Data Engineer - RegTech

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