Senior Data Engineer

**Job Description:** Required a results\-driven Senior Data Engineer with experience in designing, developing, and delivering enterprise\-scale data engineering solutions across data warehousing, big data, and cloud platforms. **Key Responsibilities \& Leadership \-** * Design and implement enterprise\-scale data architectures, including Data Warehouses and Data Lakes. * Build and maintain scalable ETL/ELT pipelines for analytics, reporting, and operational workloads. * Lead end\-to\-end data migration and modernisation programs from legacy systems to Hadoop, Spark, Databricks, and AWS platforms using Agile methodology. * Define and execute migration strategies, including data analysis, mapping, transformation, integration, validation, reconciliation, and production deployment. * Design and optimise data models, SQL queries, and Spark workloads to improve performance, scalability, and cost efficiency. * Develop automation solutions to reduce manual effort and improve operational efficiency. * Ensure data quality, consistency, governance, and compliance across enterprise data platforms. * Perform data profiling, validation, and reconciliation to ensure accuracy and reliability of data assets. * Lead technical design reviews, architecture discussions, and code reviews to ensure adherence to best practices and standards. * Manage full project lifecycle delivery, including requirements gathering, design, development, testing, deployment, and production support. * Collaborate with architects, business analysts, product owners, and clients to translate business requirements into technical solutions. * Lead and mentor data engineering teams, including task allocation, skill development, and performance management. * Identify and resolve technical and delivery blockers to ensure timely project execution. * Manage stakeholder expectations and communicate technical solutions clearly to both technical and non\-technical audiences. * Deliver both new development and production support projects in enterprise environments. * Continuously improve systems by identifying opportunities for performance, scalability, and cost optimisation. * Adapt quickly to new technologies, including AI\-enabled data platforms, modern data engineering tools, and evolving coding methodologies. * Apply modern coding practices, including modular design, reusable components, version control standards, and CI/CD\-aligned development approaches. * Maintain a strong continuous learning mindset and ability to work across evolving data and AI\-driven ecosystems. * Strong domain expertise in banking domain. **Technical Skills \-** * Data Engineering \& Platforms: Data Warehousing, Data Lakes, ETL/ELT, Data Pipelines, Data Modelling, Data Profiling, Data Migration, Data Modernisation, Data Quality, Data Governance * Databases: SQL, Teradata, Oracle, DB2, Vertica, PostgreSQL, Amazon Redshift * Big Data Technologies: Hadoop ecosystem (HDFS, Hive, Hive SQL), Apache Spark, Spark SQL, PySpark * Cloud \& Modern Data Platforms: AWS/Azure/GCP, Databricks/Snowflake/DBT * Programming \& Scripting: Python, UNIX Shell Scripting CI/CD: GitHub/ Jenkins Pay: $100,000\.00 – $150,000\.00 per year Work Location: In person