Data Engineer

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Data EngineerData

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Quick Summary

Key Responsibilities

Legacy Data Platform Support Maintain and enhance SSIS packages for data extraction, transformation, and loading Support SQL Server data warehouse (staging, ODS,

Technical Tools

Data EngineerData

Responsibilities

~1 min read

Maintain and enhance SSIS packages for data extraction, transformation, and loading
Support SQL Server data warehouse (staging, ODS, reporting layers)
Troubleshoot data issues, job failures, and performance bottlenecks
Optimize SQL queries, stored procedures, and indexing strategies
Ensure reliability of scheduled jobs via SQL Server Agent

Design and develop data pipelines using Azure Data Factory (ADF)
Ingest and organize data into Azure Data Lake (Bronze/Silver/Gold layers)
Build scalable data transformations using Databricks (Spark SQL, PySpark)
Create curated, analytics-ready datasets for Power BI
Implement Delta Lake and support data governance (e.g., Unity Catalog)

Analyze and document existing SSIS/SQL pipelines
Translate legacy ETL processes into modern ELT patterns
Support phased migration strategy (coexistence of legacy and modern platforms)
Reduce technical debt and improve pipeline maintainability
Establish standards for data modeling, naming, and architecture

Design dimensional models (fact and dimension tables) aligned to business processes
Integrate and standardize data across multiple ERP systems
Translate business requirements into scalable data solutions
Partner with stakeholders to identify high-impact use cases for data and analytics
Deliver datasets that enable reporting, forecasting, and operational insights

Implement data validation, reconciliation, and monitoring processes
Ensure data accuracy and consistency across systems during migration
Define and enforce data quality standards and controls
Support data lineage, documentation, and transparency initiatives

Work closely with business stakeholders, analysts, and BI developers
Support Power BI semantic models and reporting solutions
Communicate technical solutions in business terms
Act as a bridge between IT/data teams and business functions

Requirements

~1 min read

4–8+ years of experience in data engineering or data warehousing
Strong SQL skills (T-SQL and/or Spark SQL)
Hands-on experience with SSIS and SQL Server
Experience with Azure Data Factory (ADF) or similar tools
Experience with Databricks (Spark, Delta Lake, or similar platforms)
Solid understanding of data warehousing concepts (star schema, fact/dimension modeling)
Experience integrating data from multiple source systems (ERP experience preferred)
Proven ability to translate business requirements into technical solutions