Data Engineer

About the Role We are seeking a Data Engineer to design and build scalable data pipelines and platforms using cloud technologies. You will work on enterprise data infrastructure projects across financial services, owning end-to-end data solutions from ingestion through analytics serving. This role requires strong technical depth and the ability to collaborate across teams to deliver high-quality, governed data solutions. Key Responsibilities • Design & build data pipelines — ETL/ELT processes, data transformations, real-time streaming • Architect data platforms — design schemas, optimize performance, ensure scalability • Implement data governance — manage access control, data quality checks, metadata tracking • Support banking/financial use cases — work on transaction data, customer analytics, risk reporting • Optimize performance & costs — tune queries, manage cloud resources, balance speed vs. cost • Collaborate with teams — work with analysts, data scientists, DBAs, and architects • Document & share knowledge — write runbooks, design docs, and best-practice guides Required Qualifications • Advanced proficiency in:Snowflake OR Databricks — production experience with complex queries, performance tuningData Modeling — design normalized/dimensional schemas for analyticsCloudera OR Teradata — experience with at least one legacy/on-premises platform • 5+ years in data engineering roles • Strong SQL — write efficient, optimized queries • Python or Scala — develop data transformations and automation • Banking or financial services data experience — familiarity with regulatory requirements (AML, reporting) Recommended Skills • Experience with both a cloud platform (Snowflake/Databricks) AND a traditional warehouse (Cloudera/Teradata) • Apache Spark — distributed processing, optimization • Data governance tools — custom metadata systems, data catalogs • Cloud platforms — AWS, Azure, or GCP • Real-time data — streaming pipelines, Kafka, Flink • Agile & collaborative working environment What We’re Looking For • Hands-on builder — you’ve shipped multiple production pipelines • Detail-oriented — cares about data quality, documentation, and maintainability • Curious learner — stays current with data engineering trends • Problem solver — debugs performance issues and proposes elegant solutions • Team player — collaborates well, asks questions, shares knowledge