Data Engineer
Full-TimeHybrid
Job Description
We are seeking a Senior Data Engineer who brings more than technical execution. This role is designed for someone who can think critically, plan proactively, and take full ownership of data solutions from concept through production. The ideal candidate does not wait for direction but anticipates needs, identifies gaps, and drives outcomes that align with business objectives.
This position will play a key role in shaping and scaling a modern data ecosystem within a banking environment. You will work within a cloud-native architecture built on Microsoft Azure, Snowflake, and event-driven technologies, supporting analytics, regulatory reporting, and operational decision-making.
Responsibilities
Own end-to-end delivery of data solutions, from architecture and design through deployment, optimization, and ongoing evolution
Translate business needs into scalable data models, pipelines, and platform capabilities
Design and implement robust data pipelines using Azure Data Factory, ADLS, and Snowflake
Build and manage streaming and event-driven architectures using Redpanda
Partner with key stakeholders across lending, risk, finance, and compliance to ensure data solutions align with business and regulatory requirements
Establish and enforce data quality, lineage, and governance standards in a regulated banking environment
Optimize performance, scalability, and cost efficiency across cloud data platforms
Contribute to platform strategy, including architecture patterns, tooling decisions, and long-term roadmap
Mentor junior engineers and help raise the overall engineering standard of the team
Proactively identify opportunities to improve data accessibility, usability, and business impact
Qualifications
7+ years of experience in data engineering, with demonstrated ownership of production-grade data systems
Strong experience with Microsoft Azure data services, specifically Azure Data Factory, Azure Data Lake Storage (ADLS), and Synapse Analytics and or Microsoft Fabric
Hands-on experience with Snowflake, including data modeling, performance tuning, and cost optimization
Hands-on experience with streaming platforms such as Redpanda (or closely related technologies like Kafka)
Proficiency in Python and SQL, with experience building scalable data pipelines and transformations
Proven ability to design and implement cloud-native data architectures that are scalable, maintainable, and cost-efficient
Strong problem-solving ability with a planning-first mindset, capable of designing solutions rather than simply executing tasks
Experience working in regulated environments, preferably within banking or financial services
Preferred Skills
Experience with Azure Databricks or Spark-based processing frameworks
Familiarity with Microsoft Purview or similar data governance and lineage tools
Familiarity with PBT (Property-Based Testing) or similar testing methodologies for data systems
Experience supporting regulatory reporting, audit, or compliance-driven data initiatives
Exposure to CI/CD practices and infrastructure as code within Azure environments
Understanding of banking regulations such as GLBA, FFIEC guidance, and data handling standards
What Sets This Role Apart
This is not a ticket-driven engineering role. You will be expected to think ahead, design with intent, and take full ownership of outcomes. The right candidate will operate with a high degree of autonomy and accountability, shaping both the solution and the approach.
You will have the opportunity to own solutions end to end, influence platform direction, and play a foundational role in advancing the bank’s data capabilities.
This position will play a key role in shaping and scaling a modern data ecosystem within a banking environment. You will work within a cloud-native architecture built on Microsoft Azure, Snowflake, and event-driven technologies, supporting analytics, regulatory reporting, and operational decision-making.
Responsibilities
Own end-to-end delivery of data solutions, from architecture and design through deployment, optimization, and ongoing evolution
Translate business needs into scalable data models, pipelines, and platform capabilities
Design and implement robust data pipelines using Azure Data Factory, ADLS, and Snowflake
Build and manage streaming and event-driven architectures using Redpanda
Partner with key stakeholders across lending, risk, finance, and compliance to ensure data solutions align with business and regulatory requirements
Establish and enforce data quality, lineage, and governance standards in a regulated banking environment
Optimize performance, scalability, and cost efficiency across cloud data platforms
Contribute to platform strategy, including architecture patterns, tooling decisions, and long-term roadmap
Mentor junior engineers and help raise the overall engineering standard of the team
Proactively identify opportunities to improve data accessibility, usability, and business impact
Qualifications
7+ years of experience in data engineering, with demonstrated ownership of production-grade data systems
Strong experience with Microsoft Azure data services, specifically Azure Data Factory, Azure Data Lake Storage (ADLS), and Synapse Analytics and or Microsoft Fabric
Hands-on experience with Snowflake, including data modeling, performance tuning, and cost optimization
Hands-on experience with streaming platforms such as Redpanda (or closely related technologies like Kafka)
Proficiency in Python and SQL, with experience building scalable data pipelines and transformations
Proven ability to design and implement cloud-native data architectures that are scalable, maintainable, and cost-efficient
Strong problem-solving ability with a planning-first mindset, capable of designing solutions rather than simply executing tasks
Experience working in regulated environments, preferably within banking or financial services
Preferred Skills
Experience with Azure Databricks or Spark-based processing frameworks
Familiarity with Microsoft Purview or similar data governance and lineage tools
Familiarity with PBT (Property-Based Testing) or similar testing methodologies for data systems
Experience supporting regulatory reporting, audit, or compliance-driven data initiatives
Exposure to CI/CD practices and infrastructure as code within Azure environments
Understanding of banking regulations such as GLBA, FFIEC guidance, and data handling standards
What Sets This Role Apart
This is not a ticket-driven engineering role. You will be expected to think ahead, design with intent, and take full ownership of outcomes. The right candidate will operate with a high degree of autonomy and accountability, shaping both the solution and the approach.
You will have the opportunity to own solutions end to end, influence platform direction, and play a foundational role in advancing the bank’s data capabilities.