Data Engineer - RegTech

Job description

## **Job Description:** - As a Data Engineer you will design and implement data ingestion canonical mapping validation lineage and data processing capabilities for an enterprise platform supporting regulated workflows - You will work with architects backend engineers AI engineers QA and domain specialists to ensure data is reliable traceable governed and reusable across modules ## **Key Responsibilities:** - 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 ## **Technical Requirements:** - 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 - Strong documentation discipline and ability to collaborate with functional SMEs and engineers on data requirements ## **Preferred Skills:** Technology->Analytics - Packages->Python - Big Data,Technology->Data Engineering->Databricks,Technology->Data Services Testing->Data Warehouse Testing,Technology->ETL & Data Quality->ETL - Others