Data Engineer - RegTech

Data Engineer - RegTech

• 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. • 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