Senior Data Analyst - ALM

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines using Python (pandas, SQL Alchemy/pyodbc), SQL, Excel, and SAS.
• Optimize queries, jobs, and data models for performance, reliability, and cost; implement indexing/partitioning strategies.
• Implement and execute data quality checks, logging, alerting, and SLAs to support data pipelines; assist with incident response and root-cause analysis.
• Implement version control (Git) and code reviews; promote code and databases from dev to prod with appropriate controls.
• Partner with both upstream and downstream stakeholders to translate requirements into user stories; deliver in sprints, demo working solutions, and refine products based on customer feedback.
• Document datasets, lineage, and playbooks; create runbooks for production operations and knowledge transfer to associates.
• Enforce data governance and access controls; handle sensitive data responsibly and align with compliance standards.
• Mentor junior associates and elevate team standards through best practices in Data Ops and Agile.
• Employ an Agile philosophy to continuously improve the ALM data framework, ensuring alignment with business objectives and changing market conditions.
• Assist with projects related to ALM systems, including automation, integration with financial reporting systems, and implementation of new methodologies.
• Ensure compliance with internal policies and external regulations regarding funds transfer pricing and risk management.

• Bachelor’s degree in Computer Science, Information Systems, Data Science/Analytics, Statistics, Mathematics, Engineering, or Finance/Economics with strong quantitative coursework.
• 5+ years building and supporting data pipelines in a production environment or an equivalent combination of experience and education.
• Highly advanced Python for data engineering/analytics (pandas, SQL connectivity, packaging, job orchestration).
• Excellent verbal and written communication skills, with a desire to understand customer needs and deliver high quality products.
• Advanced SQL skills on relational platforms (e.g., SQL Server, Oracle, or Postgre
  
  SQL).
• Experience with Excel/Power Query and a proven ability to move between systems and learn new technologies.
• Hands‑on experience with Agile (Scrum/Kanban), story breakdown, sprint planning, and backlog refinement.
• Proven experience with production support in fast‑paced environments, including on‑call/after‑hours as needed.
• Solid Git workflow, CI/CD, automated testing, and code quality practices.

• Master’s in Quantitative Finance/Financial Engineering, Statistics, Data Science/Analytics, or Computer Science.
• Background in financial services; knowledge of banking products, ALM/FTP concepts is a plus.
• Familiarity with data quality frameworks and testing (e.g., Great Expectations, pytest).
• Exposure to cloud data platforms (e.g., Snowflake, Redshift, Big Query, or Azure Synapse).

• Medical with wellness incentives, dental, and vision
• HSA with company match
• Maternity and parental leave
• Tuition reimbursement
• Mentor program
• 401(k) with 6% match
• More –

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