Senior Data Engineer- Financial Servies experience required

Senior Data Engineer - Build Next-Gen Data Platforms in Financial ServicesPhiladelphia, PAOwn The Data Engine Behind Critical Financial OperationsYou'll be the data engineer who turns massive, messy operational data into clean, trusted, business-ready datasets that middle- and back-office teams can actually use. This isn't just "move data from A to B". You'll architect and build modern data platforms and pipelines that power trading operations, risk, reconciliations, and compliance across capital markets. Batch. Streaming. High-volume. Low-latency. If you've built serious data systems in financial services and want to own the next generation of platforms, we want to talk to you.What You'll Work OnYou'll sit on a Data Technologies team that partners directly with middle- and back-office application teams to:Next-generation data platforms for capital markets operationsScalable batch and streaming data pipelinesBusiness-ready data products for operations and complianceLarge-scale analytical datasets for middle- and back-office systemsHigh-performance data processing and query environmentsModern file and table formats for analytics at scaleOn-premises data platform components and integrationsYou'll work with modern data engineering technologies such as Spark, Databricks, Trino, Iceberg, Snowflake, Parquet, Apache Arrow, Polars, and Kafka, using Python as your primary development language. Your core challenge: design and optimize data platforms that stay reliable and fast even as the data and the business keep scaling.What You'll Be DoingDesigning, developing, and supporting scalable data pipelines for middle- and back-office systemsArchitecting and implementing modern data platform solutionsBuilding and optimizing large-scale batch data processing workflowsBuilding and optimizing large-scale streaming data processing workflowsCollaborating with application teams to model and transform data to meet business requirementsDelivering business-ready data products to operations and compliance stakeholdersImplementing and tuning high-volume data processing frameworksOptimizing queries and performance in large-scale analytical environmentsMonitoring data processing environments for reliability, scalability, and performanceTroubleshooting and resolving issues across data pipelines and platformsImproving robustness and efficiency of existing data workflowsProviding occasional off-hours or weekend support when neededWhat We're Looking For5+ years of experience in data engineering, data platforms, or large-scale distributed data processingStrong experience with modern data technologies such as Spark, Databricks, Trino, Iceberg, Snowflake, Parquet, Apache Arrow, Polars, and/or KafkaStrong Python development skillsHands-on experience designing and optimizing high-volume data pipelinesExperience with large-scale batch and streaming data processing frameworksProven background in query optimization and performance tuning in analytical environmentsExperience with on-premises data platforms (preferred)Industry experience within capital markets or financial services (required)Domain knowledge in operations and/or compliance within financial services (highly preferred)Ability and flexibility to provide occasional off-hours/weekend supportThe Experience That Will Really Get Our AttentionYou've been the go-to engineer when data problems get hard: distributed joins blowing up, streaming jobs lagging, analytical queries timing out, and stakeholders who still need answers on time. You know how to design data models and pipelines that work in the real world of capital markets and post-trade operations. If you've paired strong Python engineering with hands-on work in Spark- or Databricks-based platforms, dealt with on-prem constraints, and delivered high-performance datasets for operations or compliance teams, you'll stand out here.Why This Opportunity?You'll work close to the money, on the data that actually runs the business—operations, settlements, reconciliations, compliance—not vanity dashboards. You'll own substantial pieces of the data platform, from architecture through production support, with direct partnerships across middle- and back-office teams. You'll get to sharpen your skills on modern data technologies at serious scale, in a capital markets environment where performance, correctness, and reliability all matter.Important RequirementsIndustry experience within capital markets or financial services is required. Ability and flexibility to provide occasional off-hours/weekend support is required.Interested?If you're a senior data engineer who thrives on large-scale, high-impact financial data challenges, let's talk. Please send your resume to View email address on click.appcast.io.