Senior Data Engineer

Job Description

Senior Data Engineer

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Overview

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A leading financial services organization is seeking a Senior Data Engineer to join a high-performing technology team responsible for delivering enterprise data solutions that support financial reporting, operational analytics, regulatory requirements, and business decision-making.

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This role will be responsible for building and maintaining the full data lifecycle, from source system integration and ETL development through modern cloud data platforms, data warehousing, and business intelligence enablement. The ideal candidate combines deep SQL and data integration expertise with hands-on experience modernizing data environments and delivering scalable, governed analytics solutions.

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This is a hands-on engineering position focused on both maintaining critical production data processes and driving the evolution to a modern cloud-based data platform.

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Key Responsibilities

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Data Engineering & Database Development

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• Design, develop, and optimize database solutions including schemas, stored procedures, functions, views, and high-performance queries.
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• Manage database performance, indexing strategies, data modeling, and query optimization initiatives.
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• Support mission-critical reporting and operational workloads through reliable and scalable database solutions.
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• Perform troubleshooting and root cause analysis for production data issues.
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Data Integration & ETL Development

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• Build, maintain, and enhance enterprise data integration processes across internal and third-party data sources.
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• Develop scalable ETL and ELT workflows to support operational and analytical use cases.
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• Optimize existing data pipelines for performance, accuracy, and maintainability.
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• Partner with business and technology teams to onboard new data sources and requirements.
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Cloud Data Platform & Warehouse Engineering

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• Design and develop modern data warehouse and lakehouse solutions using cloud-native technologies.
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• Implement layered data architectures that transform raw data into curated, business-ready datasets.
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• Apply dimensional modeling and best practices to create scalable, reusable analytics assets.
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• Support cloud migration and modernization initiatives across enterprise data platforms.
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Business Intelligence & Semantic Modeling

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• Develop and maintain semantic models that support enterprise reporting and analytics.
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• Design security frameworks and data access controls to ensure appropriate data visibility and governance.
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• Partner with reporting and analytics teams to improve consistency, performance, and usability of business intelligence solutions.
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• Support self-service analytics initiatives and enterprise reporting standards.
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Data Quality, Governance & Production Support

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• Implement validation, reconciliation, and data quality processes throughout the data lifecycle.
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• Establish monitoring, alerting, and operational controls for critical data pipelines.
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• Maintain data lineage, governance standards, and documentation.
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• Ensure availability and reliability of data supporting finance, operations, regulatory reporting, and other business-critical functions.
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Engineering Best Practices

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• Implement version control, automated deployments, and CI/CD methodologies for data assets.
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• Create and maintain operational runbooks, technical documentation, and support procedures.
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• Support change management and release management processes.
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• Promote best practices across data engineering, governance, security, and operational support.
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Required Qualifications

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• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline.
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• 7+ years of experience in data engineering, database development, ETL development, or data integration roles.
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• Advanced experience with Microsoft SQL Server and T-SQL development.
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• Strong background in database design, performance tuning, indexing, and query optimization.
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• Experience building and supporting enterprise ETL and ELT solutions.
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• Hands-on experience implementing cloud-based data warehouses or lakehouse platforms.
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• Strong understanding of dimensional modeling, star schema design, and modern analytics architectures.
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• Experience supporting highly available production environments with strict operational and compliance requirements.
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• Strong troubleshooting, analytical, and problem-solving abilities.
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Technical Skills

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• Microsoft SQL Server, T-SQL, stored procedures, database optimization, and performance tuning.
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• Enterprise ETL and ELT development tools and frameworks.
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• Modern cloud data platforms, lakehouse architectures, and data warehousing solutions.
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• Data modeling, dimensional design, and analytics engineering best practices.
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• Power BI development, semantic modeling, DAX, and data security concepts.
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• Experience implementing row-level security and data governance controls.
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• Working knowledge of Python for data processing, automation, and engineering tasks.
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• Git, version control, deployment pipelines, and CI/CD methodologies.
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Preferred Qualifications

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• Experience within financial services, banking, capital markets, asset management, or other regulated industries.
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• Experience supporting finance, accounting, treasury, operational reporting, or regulatory reporting functions.
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• Experience with enterprise ERP integrations and data consolidation initiatives.
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• Exposure to cloud migration, data modernization, or digital transformation programs.
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• Experience supporting business intelligence and self-service analytics environments.
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• Relevant cloud, analytics, or data engineering certifications.
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What You'll Bring

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• Strong data engineering fundamentals combined with modern cloud platform expertise.
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• A proactive, solution-oriented mindset focused on reliability and continuous improvement.
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• Excellent communication and stakeholder management skills.
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• Experience balancing strategic modernization efforts with day-to-day production support responsibilities.
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• Strong attention to detail and commitment to data quality.
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• The ability to work independently while collaborating effectively across business and technology teams.
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This is an excellent opportunity for a senior-level data professional looking to play a key role in modernizing enterprise data architecture, building scalable analytics platforms, and delivering high-impact solutions that support critical business operations and decision-making.