Analytics Data Engineer (ETL, Data Modeling, KPI Framework)
Overview
We are seeking a highly experienced Data Platform Engineer to build and maintain the core data infrastructure that powers our analytics and reporting systems. This role is responsible for developing ETL pipelines, managing and optimizing PostgreSQL databases, standardizing data structures, and creating a unified library of analytical logic and KPIs. The ideal candidate is a senior-level engineer with deep experience in Python, SQL, data modeling, and the development of reusable, API-ready data services. This is a hands-on, high-impact technical role with broad ownership of our data environment.
Key Responsibilities
1. ETL Engineering & Data Acquisition
• Design, build, and maintain automated ETL pipelines for multiple external and internal data sources.
• Develop ingest processes using Python and SQL to ensure reliable, repeatable, and scalable data flows.
• Standardize incoming data formats and apply robust validation, cleansing, and transformation logic.
• Implement exception handling and data quality monitoring across all ingestion workflows.
2. Database Development & Management
• Architect, maintain, and optimize PostgreSQL schemas and relational models.
• Build indexes, materialized views, stored functions, and high-performance query structures.
• Ensure referential integrity and consistent relationships across all key data entities.
• Manage versioning, migrations, and documentation of database structures.
3. KPI Library & Analytical Logic
• Develop a centralized library of KPIs, calculations, and analytical rules used across reporting and product features.
• Implement KPI logic in both Python modules and SQL-based functions for hybrid f lexibility.
• Maintain consistent definitions and standardized formulas across all analytical outputs.
• Collaborate with engineering and analytics teams to ensure shared access to validated metrics.
4. Data Object Modeling & Standardization
• Create reusable object models for key data entities, including assets, sites, transactions, events, and classifications.
• Maintain clean, well-structured dimension and reference tables that support dynamic reporting.
• Document and enforce data definitions, taxonomies, and business logic across the platform.
• Ensure that data objects remain consistent as new features, sources, and use cases emerge.
5. API-Ready Data Services
• Develop standardized query layers and data access patterns for use by internal applications.
• Package data outputs into reusable, parameterized functions that support dynamic dashboards and reporting tools.
• Optimize query performance for API calls and high-volume reporting workloads.
• Work with application engineers to integrate validated data endpoints into product features.
Required Skills & Experience
• 7+ years of experience in data engineering, ETL development, or data platform roles.
• Expert-level proficiency in Python, including data transformation libraries and modular design.
• Advanced proficiency in PostgreSQL, including schema design, SQL optimization, and procedural SQL.
• Strong background in designing and maintaining ETL pipelines for diverse data sources.
• Experience building analytical metrics, KPI calculation frameworks, or reusable logic libraries.
• Solid understanding of relational modeling, dimensional modeling, and metadata management.
• Experience developing data services or backend logic consumed by APIs or reporting tools.
• Ability to work independently, manage complex technical systems, and communicate clearly with technical and non-technical teams. Preferred
Qualifications
• Experience with workflow orchestration tools (Airflow, Prefect, Dagster, etc.).
• Background in operational analytics, compliance data, or multi-source data harmonization.
• Experience with API design or integrating data layers with web applications.
• Familiarity with BI tools such as Tableau or Metabase.
• Exposure to SaaS data architectures or multi-tenant systems. What This Role Offers
• The opportunity to build and own a complete data foundation for a growing technology platform.
• Direct influence on system architecture, data quality, and analytical capabilities.
• A role that combines ETL, modeling, KPI development, and API-driven data delivery.
• A high-visibility position with meaningful impact on product performance and client deliverables.
