INFOPARK

Database Architect

Job Description / Duties and Responsibilities

• Design and optimize enterprise data solutions and Azure SQL databases.
• Collaborate with DBAs, Solution Architects, Product Owners, and development teams.
• Support microservices by implementing efficient and scalable data architectures.
• Improve data quality, governance, performance, and reporting capabilities.
• Translate business requirements into data-driven solutions and best practices.
• 10+ years of experience in data consulting, data architecture, or related roles.
• Strong hands-on experience with Microsoft SQL Server, including performance tuning and data modeling.
• Excellent communication and stakeholder collaboration skills.
• Proficiency in ETL and data wrangling concepts
• OLAP and OLTP experience

Preferred Qualifications

• Experience in the automotive industry.
• Knowledge of Dealer Management Systems (DMS) is a strong plus.
• Strong understanding of data attributes to business processes and data relationships across business areas

SSE/Lead Engineer- python

Job Purpose-
Be a Lead/Senior Engineer in Python Technology.

Job Description-
▪ Good hands-on knowledge in Django or Flask.
▪ Experience in designing & developing Microservices based applications, Unit testing using Pytest or
similar, DevOps and Agile practices, Code Reviews.
▪ Good development experience of at least 6+ years in Python + one amongst .NET, NodeJS, Angular
technologies
▪ Ability to write code in an efficiently structured and modularized manner.
▪ Good Understanding of one of the frameworks - Flask, Django etc.
▪ Experience with integrating code with Databases, front end application etc.
▪ Knowledge on various databases - such as MySQL, MariaDB and working experience on integrations with
NoSQL databases as well.
▪ Working experience on templating languages such as Jinja2.
▪ Experience on working with AWS, Azure APIs (Python) is an additional good to have skill.
▪ Passion for best design and coding practices and a desire to develop new bold ideas
▪ Good understanding of code versioning (Git, SVN etc.)
▪ Nice to have: Working experience in DevOps.

Duties and Responsibilities-

▪ Take senior/lead engineer role in managing tasks in a sprint, reviewing the code of team members and
ensuring first time quality of code
▪ Write “clean”, well-designed code
▪ Capability to understand user stories, translate that into technical specifications and convert this into
working code.
▪ Follow modern agile based development process including TDD based unit testing
▪ Produce detailed specifications
▪ Troubleshoot, test and maintain the core product software and databases to ensure strong optimization
and functionality
▪ Contribute in all phases of the development lifecycle
▪ Follow technology best practices.
▪ Develop and deploy new features to facilitate related procedures and tools if necessary.

Any Additional Information/Specifics-

- Participate in the full product development cycle, including brainstorming, release planning and estimation,
implementing and iterating on code, coordinating with internal and external clients, internal code and design
reviews, MVP and production releases, quality assurance, and product support.
- Highly effective and thrive in a dynamic environment
- Comfortable with proactive outward communication and technical leadership and positive about accepting
challenges.
- To adhere to ISMS policies and procedures.

Databricks Architect

Total Experience :10+years

Work Location : Trivandrum /Kochi Only

The Databricks Lead / Architect will own end-to-end solution design and provide hands-on technical
leadership across Databricks and cloud data platforms. The role involves translating business and data
requirements into scalable architectures, establishing engineering standards, guiding development
teams, driving modernization and migration initiatives, and working closely with clients, architects and
technology leadership.

Key Responsibilities
• Design and implement enterprise-scale Databricks Lakehouse architectures.
• Define architecture across Azure, AWS and GCP based on business and technical requirements.
• Design data ingestion, transformation and processing using Databricks, Spark, PySpark, SQL and
Python.
• Establish Lakehouse architecture, including Delta Lake, Medallion Architecture and data
modelling.
• Design batch and real-time data processing and integration solutions.
Job Description
• Architect and implement Databricks Workflows, Jobs, Unity Catalog and governance
capabilities.
• Define data security, access control, lineage, quality, monitoring and governance standards.
• Design scalable and optimized solutions for performance and cloud cost.
• Lead migration and modernization of legacy data platforms to Databricks.
• Integrate Databricks with cloud-native services across Azure / AWS / GCP.
• Establish CI/CD, Git, DevOps and deployment standards for data engineering.
• Provide technical leadership through design reviews, code reviews and engineering standards.
• Guide and mentor Data Engineers and technical teams.
• Conduct POCs and evaluate new Databricks/cloud capabilities.
• Work with business stakeholders, project managers and enterprise architects to translate
requirements into technical solutions.
• Support estimation, solution proposals, technical presentations and client discussions.
• Adhere to the Information Security Management policies and procedures.

Job Specification / Skills and Competencies

Mandatory Skills
• 10+ years of experience in Data Engineering / Data Architecture.
• Strong hands-on experience with Databricks and Lakehouse architecture.
• Strong knowledge of Apache Spark, PySpark, Python and SQL.
• Experience with Delta Lake and Medallion Architecture.
• Strong experience in data modelling, ETL/ELT and data integration.
• Experience designing scalable batch and real-time data solutions.
• Strong knowledge of at least one major cloud platform: Azure, AWS or GCP.
• Understanding of cloud data services and integration patterns.
• Experience with Databricks Workflows/Jobs and Unity Catalog.
• Strong understanding of data security, governance, quality and lineage.
• Experience with CI/CD, Git and DevOps practices.
• Strong solution architecture and technical leadership skills.

MS Fabric Lead

Job Purpose (both Onsite / Offshore)
Lead the design, development and delivery of Microsoft Fabric-based data solutions, ensuring high
quality, scalable and performant data engineering and analytics implementations. The role will provide
hands-on technical leadership to the delivery team, establish engineering best practices, and work with
architects and stakeholders to translate requirements into effective Fabric solutions.

Job Description / Duties and Responsibilities
The Microsoft Fabric Lead will lead technical implementation across Microsoft Fabric and Azure,
covering data ingestion, transformation, Lakehouse, Warehouse, data pipelines, Spark-based
processing and Power BI. The role will guide developers, perform technical reviews, troubleshoot
complex issues and ensure solutions meet defined architecture, security, performance and quality
standards.
The role will collaborate with the Fabric Architect, project managers, business stakeholders and
engineering teams to deliver end-to-end data and analytics solutions.

DUTIES & RESPONSIBILITIES
• Lead development and implementation of Microsoft Fabric solutions using OneLake, Lakehouse, Fabric Warehouse and Data Factory/Pipelines.
• Design and develop scalable ETL/ELT data pipelines and data transformation processes.
• Develop and optimize SQL, PySpark/Python and Spark workloads.
• Implement Medallion architecture and appropriate data modelling patterns.
• Lead development of Power BI semantic models, datasets and reports, including Direct Lake/Import/DirectQuery where applicable.
• Perform code reviews, technical reviews and ensure adherence to development standards.
• Troubleshoot performance, data quality and integration issues and provide technical solutions.
• Implement data security, governance, quality and monitoring practices defined by the architecture.
• Support data-platform migration and modernization initiatives.
• Work closely with the Fabric Architect to translate solution architecture into implementation designs.
• Mentor developers and provide technical guidance to the delivery team.
• Participate in POCs, technical estimations, design discussions and client/stakeholder meetings.
• Ensure timely delivery of technically robust and production-ready solutions.
• Adherence to company policies, procedures, and relevant regulations in all duties.

Job Specification / Skills and Competencies
• Strong hands-on experience with Microsoft Fabric.
• Fabric Lakehouse, OneLake and Fabric Warehouse.
• Fabric Data Factory / Data Pipelines.
• Strong SQL skills.
• Hands-on PySpark / Spark / Python experience.
• Strong understanding of ETL/ELT and data engineering.
• Power BI development and semantic modelling.
• Experience with Direct Lake, Import and/or DirectQuery.
• Azure data services, preferably ADLS, Azure SQL, Synapse and Azure Data Factory.
• Data modelling, data quality and data integration.
• Experience working in Agile/DevOps delivery environments.
• Microsoft Fabric Data Engineering
• Lakehouse and Medallion Architecture
• SQL development and performance optimization
• Power BI semantic models and enterprise reporting
• Data migration and modernization
• CI/CD and deployment practices
• Technical troubleshooting and performance tuning
• Technical leadership, mentoring and code reviews
• Ability to work with architects and translate designs into implementation

MS Fabric Architect

Job Purpose (both Onsite / Offshore)
Lead the architecture, design and delivery of enterprise-scale Microsoft Fabric data platforms,
enabling modern data engineering, analytics, BI and AI capabilities. The role will define scalable, secure
and cost-effective data architectures, drive cloud/data modernization, and provide technical
leadership to engineering and delivery teams.

Job Description / Duties and Responsibilities
The Microsoft Fabric Architect will own end-to-end solution architecture across Microsoft Fabric and
Azure, translating business and data requirements into robust technical solutions. The role will
establish architecture standards and patterns covering data ingestion, transformation, storage,
analytics, governance, security and consumption.
The architect will work closely with business stakeholders, data engineers, BI teams, cloud architects
and technology leadership, and will provide hands-on technical guidance throughout the solution
lifecycle.
DUTIES & RESPONSIBILITIES
• Define end-to-end Microsoft Fabric architecture using OneLake, Lakehouse, Fabric Warehouse,
Data Factory/Data Pipelines, Spark and Real-Time Intelligence.
• Design scalable batch and real-time data ingestion, processing and analytics solutions.
• Establish data architecture patterns including Medallion architecture, dimensional modelling
and enterprise semantic models.
• Design and govern Power BI solutions, including semantic models and appropriate use of Direct
Lake, Import and DirectQuery.
• Lead modernization/migration initiatives from legacy and cloud data platforms such as SQL
Server, Synapse, Snowflake, Teradata and Databricks.
• Define standards for security, governance, data quality, lineage, monitoring, performance and
cost optimization.
• Guide engineering teams on Fabric implementation, coding standards, CI/CD and DevOps
practices.
• Conduct architecture reviews, POCs and technology evaluations and recommend appropriate
solutions.
• Collaborate with stakeholders to understand requirements, explain technical trade-offs and
drive architecture decisions.
• Mentor data engineers, developers and architects and act as the technical authority for Fabric
solutions.
• Adhere to the Information Security Management policies and procedures.

Job Specification / Skills and Competencies
Essential Technical Skills
• Strong hands-on experience in Microsoft Fabric architecture and implementation.
• Expertise in OneLake, Lakehouse, Fabric Warehouse and Fabric Data Factory/Pipelines.
• Strong knowledge of Spark/PySpark, SQL and Python.
• Strong Power BI architecture, semantic modelling and DAX knowledge.
• Good understanding of Direct Lake, Import and DirectQuery.
• Strong Azure data platform knowledge including ADLS, Azure SQL, Synapse and Azure Data
Factory.
• Experience with enterprise ETL/ELT, data modelling, data governance and data security.
• Experience designing both batch and streaming data solutions.
Architecture & Professional Competencies
Job Description
• Enterprise Data & Cloud Architecture
• Solution Design and Technology Evaluation
• Data Platform Modernization & Migration
• Performance and Cost Optimization
• Security, Governance and Data Quality
• Strong analytical and problem-solving skills
• Excellent communication and stakeholder-management skills
• Ability to lead, influence and mentor technical teams

Snowflake Architect

Skills – Mandatory - Snowflake, SQL, ETL/ELT, CICD
Skills - Primary - Snowflake, SQL, ETL, CICD
Skills - Good to have - Azure/AWS, PySpark/ Python , Databricks
Qualification -Bachelor’s Degree
Total Experience - 10+ years

Relevant Experience - 7+ years

Work Location- Kochi/TVM

Expected Date of Onboarding - Immediate

Job Purpose (both Onsite / Offshore)

Lead the architecture, design and delivery of enterprise-scale Snowflake data platforms, with a strong focus on data warehouse modernization and migration. The role will drive migration from legacy appliances and databases to Snowflake, while ensuring scalable, secure, performant and cost-effective data solutions.

Job Description / Duties and Responsibilities

The Snowflake Architect will provide end-to-end technical leadership for Snowflake implementations, modernization and migration programs. The role requires strong understanding of legacy data platforms, migration strategies, data modelling, ETL/ELT, performance optimization and cloud architecture. The candidate should be able to assess existing platforms, define migration strategy and target architecture, lead technical implementation, address data and application dependencies, and ensure successful migration with minimal business disruption.

Key Responsibilities

• Design and implement enterprise-scale Snowflake architectures.

• Lead migration and modernization initiatives from legacy data platforms to Snowflake.

• Assess source platforms, workloads, data models, stored procedures, ETL processes and dependencies to define migration strategy.

• Develop migration frameworks, assessment approaches, estimation models and migration roadmaps.

• Design Snowflake data models including dimensional, normalized and Data Vault approaches where appropriate.

• Develop scalable ELT/ETL pipelines and data integration solutions.

• Optimize Snowflake workloads for performance, scalability and cost.

• Define Snowflake architecture including warehouses, databases, schemas, roles, resource management and workload isolation.

• Implement security, access control, governance, data quality and auditing standards.

• Design data ingestion from relational databases, files, APIs and enterprise applications.

• Identify and resolve data type, SQL compatibility, performance and data reconciliation challenges during migration.

• Establish CI/CD and DevOps practices for Snowflake development and deployment.

• Work with cloud teams across Azure, AWS and/or GCP to implement cloud-native data architectures.

• Provide technical leadership through architecture reviews, design reviews and code reviews. • Mentor Snowflake developers and data engineers.

• Conduct POCs and evaluate Snowflake capabilities and migration tools.

• Collaborate with business stakeholders, enterprise architects, project managers and client teams. Support solutioning, technical proposals, estimation and client presentations.

• 10+ years of experience in Data Engineering / Data Architecture / Data Warehousing. • Strong hands-on experience with Snowflake and enterprise data warehouse architecture.

• Proven experience leading data warehouse migration and modernization programs.

• Strong experience migrating from Teradata and/or Oracle to Snowflake.

• Strong SQL and data modelling skills.

• Experience with ETL/ELT, data integration and migration frameworks.

• Strong understanding of Snowflake architecture, warehouses, storage, compute and workload management.

• Experience with Snowflake security, RBAC, governance and data sharing.

• Strong understanding of performance tuning and Snowflake cost optimization.

• Experience with data reconciliation, validation and migration testing.

• Experience with cloud platforms — Azure, AWS and/or GCP.

• Strong technical leadership and stakeholder management skills.

Good to Have

• Databricks

• IICS (Informatica Intelligent Data Management Cloud)

• Azure Data Factory / AWS Glue / GCP Dataflow

• Apache Spark / PySpark

• Kafka / Event Streaming

• dbt • Power BI / Tableau

• Terraform / Infrastructure as Code

• Data Vault / Data Mesh

• Experience migrating from other appliances/databases such as Netezza, Greenplum, SQL Server or DB2

• Experience with automated migration/conversion tools

• Snowflake certifications

• Experience with large enterprise / multi-cloud migration programs

Lead AI Engineer

We are seeking a hands-on Lead AI Engineer to build, integrate, and operationalize Agenitc AI
capabilities, pre-dominantly with Gen AI. This is a core engineering role responsible for day-to-day
implementation of AI features using AWS-native tooling.


Total Experience:8+
Work Location: TVM/Kochi/Remote


AI Engineering
• Build agentic solution with conversational agents at front end & agentic automation for data
retrieval at the backend.
• Build Text to SQL AI capability
• Build Graph Database from SQL as well as unstructured data
• Build and optimize RAG pipelines, Graph RAG capabilities etc
• Evaluate LLMs (primarily AWS Bedrock based, additionally other Cloud and on-prem LLMs) for
performance, scaling & cost perspectives
• Knowledge on GPU based LLM installation/management is a plus
• Knowledge of MLOps and methodologies of model/agentic deployment is requisite

Backend Development
Develop scalable services using:
• AWS OpenSearch Service
• AWS S3
• Amazon DynamoDB
• AWS CloudWatch
• Deploy via:
• AWS Lambda
• Amazon API Gateway
• Amazon CloudFront

Model Optimization
• Prompt engineering
• Retrieval tuning
• Latency optimization
• Output quality improvement

Mandatory Skills: -
Python, multi-LLM system, RAG, AWS Lambda, Amazon API Gateway, Claude models, Bedrock-hosted models (AWS Bedrock, AWS Bedrock Knowledgebase)