- Minimum 7 years of experience in data engineering, ETL/ELT development, data warehousing, data platform engineering or related roles.

- Strong SQL skills and hands-on experience with relational databases such as PostgreSQL, SQL Server, Oracle or MySQL.

- Experience designing ingestion pipelines, transformations, validation rules, data quality checks and source-to-target mapping specifications.

- Understanding of data modeling, canonical models, metadata, lineage, audit fields, reconciliation and data quality concepts.

- Experience with Python, Spark, Databricks, Azure Data Factory, dbt, Airflow or equivalent data engineering tools is preferred.

- Ability to work with structured, semi-structured and file-based data formats such as CSV, JSON, Excel, XML and Parquet.

- Robust documentation discipline and ability to collaborate with functional SMEs and engineers on data requirements.

- Design and build data ingestion pipelines for files, APIs, SFTP sources, databases and enterprise data extracts.





- Implement canonical data models, source-to-target mapping, transformation rules, validation checks, rejected-record handling and lineage capture.

- Develop data quality checks, reconciliation routines, control result tables, exception datasets and metadata structures for auditable data processing.

- Work with PostgreSQL, SQL, object storage, data lake patterns, ETL/ELT tools and batch processing frameworks as needed.

- Partner with AI engineers to provide clean, contextual and grounded data for AI summaries, narratives, retrieval and explanations.

- Create data dictionaries, mapping specifications, interface contracts, test datasets and data-quality documentation.

- Support performance tuning, partitioning, indexing, data retention, archival and privacy-aware data handling.

- Work with QA teams to defi

📌 Data Engineer - RegTech (Bengaluru)
🏢 Infosys
📍 Bengaluru