Project Overview:

Botsford Associates is supporting the Chief Data Office of a leading financial institution on a strategic initiative to develop a centralized information management platform. This platform will enhance the bank's ability to "Know Your Data, Govern Your Data, and Use Your Data” by establishing a common business language, clarifying ownership and accountability, and enabling greater transparency and trust in enterprise data.

Role Summary:

We are seeking a Senior Data Engineer to design and implement scalable, reusable data pipelines and foundational frameworks that will power this enterprise-wide transformation. This individual will work across business and technology stakeholders to ensure clean, trusted, and ready-to-use data is ingested and maintained within the new platform, while adhering to data governance standards and technical best practices.

Key Responsibilities:

• Develop scalable ETL pipelines using Python to support ingestion, transformation, standardization, and delivery of clean data to the centralized platform.
• Integrate data from multiple sources, including S3-based storage systems and external/internal REST APIs.
• Build reusable components for data validation, control logging, exception handling, and quality checks.
• Design service layers to enable seamless data consumption by downstream analytics and business systems.
• Collaborate with data stewards and business analysts to understand critical data elements and ensure proper lineage and metadata integration.
• Optimize data structures (e.g., Parquet) and pipeline performance across large-scale datasets.
• Contribute to the onboarding and configuration of enterprise data tooling (e.g., data catalogs, lineage tracking, data quality monitoring).
• Ensure compliance with enterprise architecture and data governance policies throughout the development lifecycle.

Required Skills & Experience

• Expert-level experience in core Python development, particularly for back-end and data engineering use cases.
• Proficiency with data ingestion and integration, including extracting data from S3 storage systems and REST APIs.
• Solid experience in ETL pipeline design for data transformation, harmonization, and standardization.
• Background in building service layers/APIs to expose data to consumer applications.
• Familiarity with Parquet format and optimizing it for performance in large-scale data environments.
• Knowledge of metadata integration, data lineage, and governance frameworks is a strong asset.