Senior SQL and ETL Engineer | Remote

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This role is for a Senior SQL and ETL Engineer, fully remote for 12+ months, offering a competitive pay rate. Key skills include expertise in SQL, ETL tools, data modeling, and Python/PySpark, with experience in data warehouse architecture and big data technologies required.

• Strong expertise in SQL, PL/SQL, and T‑SQL with advanced query tuning, stored procedure optimization, and relational data modelling across Oracle, SQL Server, Postgre
  
  SQL, and MySQL.
• Proficiency in modern ETL/ELT tools including Azure Synapse Analytics, Azure Data Factory, and SSIS, with the ability to design scalable ingestion, transformation, and loading workflows.
• Ability to design and implement data warehouse data models (star schema, snowflake, dimensional hierarchies) and optimise models for analytics and large‑scale reporting.
• Strong understanding of data integration, data validation, cleansing, profiling, and end‑to‑end data quality processes to ensure accuracy and consistency across systems.
• Knowledge of enterprise data warehouse architecture, including staging layers, data marts, data lakes, and cloud‑based ingestion frameworks.
• Experience applying best practices for scalable, maintainable ETL engineering, including metadata‑driven design and automation.
• Proficiency in Python and PySpark (and familiarity with Shell/Perl) for automating ETL pipelines, handling semi‑structured data, and transforming large datasets.
• Experience handling structured and semi‑structured data formats (CSV, JSON, XML, Parquet) and consuming REST APIs for ingestion.
• Knowledge of data security and compliance practices, including credential management, encryption, and governance in Azure.
• Expertise in optimising ETL and data warehouse performance through indexing, partitioning, caching strategies, and pipeline optimisation.
• Familiarity with CI/CD workflows using Git/Git Hub Actions for ETL deployment across Dev, QA, and Production environments.
• Ability to collaborate with analysts and business stakeholders, translating complex requirements into actionable datasets, KPIs, and reporting structures.
• Experience developing and optimising SQL, PL/SQL, and T‑SQL logic, including stored procedures, functions, performance tuning, and advanced relational modelling across Oracle and SQL Server.
• Experience working with mainframe systems for data extraction, mapping, and conversion into modern ETL/ELT pipelines.
• Experience designing, orchestrating, and deploying ETL/ELT pipelines using Azure Synapse Analytics, Azure Data Factory, SSIS, and Azure Dev Ops CI/CD workflows.
• Experience building and maintaining enterprise data warehouses using Oracle, SQL Server, Teradata, or cloud data platforms.
• Experience working with big data technologies such as Apache Spark, PySpark, or Hadoop for large‑scale data transformation.
• Experience integrating structured and semi‑structured data (CSV, XML, JSON, Parquet) and consuming APIs using Python/PySpark.
• Experience supporting production ETL operations, troubleshooting pipeline failures, conducting root‑cause analysis, and ensuring SLAs for daily, monthly, or regulatory reporting workloads.

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