Data Engineer

TVS Credit Services Ltd; Kamrup Metropolitan; On-site; INR 600,000 - 1,000,000; Full time

Job summary

TVS Credit Services Ltd is looking for a Data Engineer to design and build scalable data platforms that enable analytics, reporting, and advanced data use cases. This role requires hands-on experience in data engineering practices, including Data Modeling, Data Warehousing, and SQL optimization.

The ideal candidate should have a Bachelor's degree in Computer Science or a related field, along with 1 to 4 years of experience in relevant roles. The position is based in Kamrup Metropolitan, Assam, India.

Qualifications

• 1 to 4 years of experience in Data Engineering or related roles.
• Hands-on experience in data modeling and Data Mart development preferred.

Responsibilities

• Design and build scalable data platforms for analytics and reporting.
• Develop and maintain enterprise Data Warehouses and Data Marts.
• Build scalable ETL/ELT pipelines for structured and unstructured data.

Skills

Data Modeling & Data Warehousing

SQL optimization

Python

Apache Spark

Cloud Platforms (AWS, OCI)

Education

Bachelor's degree in Computer Science, Engineering, IT, or related field

Tools

SQL

Apache Airflow

Docker

Job description

We are seeking a Data Engineer to design and build scalable data platforms that enable analytics, reporting, and advanced data use cases. The role has a strong focus on Data Modeling, Data Warehousing, and Data Mart development, ensuring high-performance, business-ready data solutions.

The ideal candidate will have hands-on experience in modern data engineering practices, SQL optimization, and cloud-based data platforms.

Key Responsibilities

Data Modeling & Data Warehousing

• Design conceptual, logical, and physical data models aligned with business requirements
• Implement dimensional modeling techniques, including:
  • Star Schema
  • Snowflake Schema
  • Fact and Dimension modeling
  • Slowly Changing Dimensions (SCD)
  • Data Vault concepts
• Design, develop, and maintain enterprise Data Warehouses and Data Marts
• Build business-centric Data Marts optimized for analytics and reporting
• Define and enforce data governance standards, data quality, and metadata management practices

SQL Development & Optimization

• Develop complex SQL and PL/SQL programs, including procedures, functions, packages, and triggers
• Perform SQL tuning and query optimization for large-scale transactional and analytical workloads
• Analyze execution plans and optimize database performance
• Design and implement:
  • Partitioning strategies
  • Indexing frameworks
  • Materialized views
  • Data archival mechanisms

Data Engineering & Pipeline Development

• Build and manage scalable ETL/ELT pipelines for structured and unstructured data
• Develop data ingestion frameworks using APIs, batch processes, and streaming sources
• Work across Data Lake Data Warehouse Data Mart architecture
• Perform data transformation and enrichment using tools such as SQL, Spark, and DBT

Cloud Data Engineering

• Design and implement cloud-native data solutions using Oracle Cloud Infrastructure (OCI) and AWS
• Leverage cloud services for storage, compute, and database systems
• Participate in cloud migration and modernization initiatives
• Build scalable and cost-effective cloud data platforms

Modern Data Technologies & Integration

• Develop real-time and streaming pipelines using event-driven architectures (e.g., Kafka)
• Create and manage REST APIs and data services for system integration
• Work with modern data platforms such as Snowflake, Databricks, or similar
• Utilize workflow orchestration tools such as Apache Airflow

Advanced Analytics & Innovation

• Prepare datasets for analytics and machine learning use cases
• Support AI/ML and emerging GenAI applications by providing high-quality data layers
• Contribute to proof-of-concepts (POCs) and innovation initiatives

Data Quality, Governance & Performance

• Implement data quality checks, monitoring, and validation frameworks
• Ensure proper data governance, lineage, and cataloging
• Optimize performance of data pipelines, queries, and reporting systems
• Troubleshoot and resolve data-related issues across systems

Collaboration & Continuous Improvement

• Work closely with business stakeholders, analysts, and data scientists
• Translate business requirements into scalable data solutions
• Continuously evaluate and adopt new tools and technologies in the data ecosystem

Qualifications

• Bachelors degree in Computer Science, Engineering, IT, or related field

Experience

• 1 to 4 years of experience in Data Engineering, Data Warehousing, or related roles
• Hands‑on experience in data modeling and Data Mart development preferred

Technical Skills

• Strong expertise in Data Modeling & Data Warehousing concepts
• Programming: Python, SQL, PL/SQL, Shell scripting
• SQL expertise in query optimization and performance tuning
• Data Processing: Apache Spark, ETL/ELT frameworks
• Workflow orchestration: Apache Airflow, DBT
• Cloud Platforms: AWS and Oracle Cloud (OCI)
• Data Platforms: Snowflake, Databricks or similar modern warehouses
• Databases: Oracle, MS SQL, and NoSQL databases
• Streaming Technologies: Kafka / event-driven systems
• API Development: RESTful APIs and integrations
• Containerization: Docker (Kubernetes is a plus)
• Data Architecture: Data Lake, Data Warehouse, Data Mart, Data Vault
• Exposure to AI/ML workflows and GenAI concepts is an added advantage
• Familiarity with DevOps/DataOps (CI/CD, version control, automation)

Key Competencies

• Strong analytical and problem-solving skills
• High attention to detail and data accuracy
• Ability to translate business needs into scalable data solutions
• Strong collaboration and communication skills
• Adaptability to learn and work with emerging technologies