Paloma Health - Data Engineer
Requirements
• Bachelor's or master's degree in Computer Science, Engineering, or a related field. • Four years of hands-on experience in data engineering or related roles, with a proven track record of building and maintaining production-grade data pipelines • Four years • Able to communicate clearly and efficiently with all internal teams • SQL, including complex queries, window functions, and performance optimisation. • Google BigQuery, including table design, partitioning, clustering, and query performance tuning • Dataform or equivalent transformation frameworks (dbt, etc.), writing SQLX, managing dependencies, and maintaining modular, well-tested transformation logic • Solid understanding of ETL/ELT pipeline design, including incremental loads, idempotency, error handling, and pipeline monitoring • Working with event-driven or streaming data pipelines (Pub/Sub, Kafka, or equivalent) • Python or JS for data pipeline scripting, transformation logic, or tooling • Version control (Git) and collaborative engineering workflows • Strong attention to data quality, experience implementing data validation, testing, and alerting within pipelines • Proven ability to collaborate cross-functionally in translating business and financial reporting requirements into reliable data models, and supporting non-technical stakeholders in getting the most out of the data warehouse • Experience ingesting and processing structured and unstructured files (CSV, JSON, XML, Parquet, PDF) from a variety of sources, including cloud storage buckets and third-party exports. • Desired but not essential skills and experience include: • Broader Google Cloud Platform ecosystem, like Cloud Run, Cloud Functions, Cloud Storage, Pub/Sub, and Cloud Scheduler • Data orchestration tools such as Cloud Composer (Airflow), Prefect, or equivalent • Looker/Data Studio and “Conventional analytics” (aka. BQ agenta) • Building or maintaining a data warehouse in a regulated or healthcare environment • GDPR and data privacy requirements as they apply to data pipelines handling personal or clinical data • Working alongside product and clinical teams to translate business questions into data models and metrics • Familiarity with data lake concepts and architecture, organising raw, cleansed, and curated data layers (bronze/silver/gold or equivalent), and working with large volumes of semi-structured data before it reaches the warehouse
Responsibilities
• Collaborate with cross-functional teams, including commercial product, operations, AI, engineering, finance, and Business Intelligence (BI), to understand business data needs and continuously improve our data warehouse to support them. This includes: • Design, build, and maintain ELT pipelines: own the end-to-end lifecycle of data pipelines that move, transform, and land data reliably into the warehouse, using Dataform and BigQuery as the core of the transformation layer. • Design, build, and maintain ELT pipelines • Own and evolve the data warehouse structure: maintain a well-organised, documented, and performant BigQuery warehouse that serves business needs. This includes data modelling, schema design, partitioning strategy, and ongoing cost and performance optimisation. • Own and evolve the data warehouse structure • Build and maintain reporting infrastructure: translating business and financial reporting requirements into reliable datasets and data models, ensuring stakeholders have accurate, timely, and trustworthy data to inform decision-making. • Build and maintain reporting infrastructure • Ingest and standardise data from diverse sources: own the ingestion of structured and unstructured files (CSV, JSON, clinical exports, third-party feeds) from a variety of sources including transactional Databases, cloud storage, and external APIs, applying robust validation, error handling, and schema management across the raw and curated data layers. • Ingest and standardise data from diverse sources • Champion data quality, governance, and documentation: implement and maintain data quality checks, testing frameworks, and alerting across pipelines; enforce data governance standards including access controls, PII handling, and lineage tracking; and ensure the warehouse is well-documented so that any team member can understand and trust the data they are working with. • Champion data quality, governance, and documentation
Benefits
• You will be part of a mission-driven organisation that’s transforming access to autism and ADHD care in England. For all employees, we offer: • A strong and positive culture that prioritises team building, transparency, and career development. This includes protected time and budget for team connection and learning. • Comprehensive compensation, including: • Competitive compensation • Annual salary reviews, ensuring they are competitive • 5% employer pension contribution • Equity compensation through Share Options in Paloma Health • Optional Private Medical Insurance and Employee Assistance Programme • A unique annual leave benefits package which includes: • 37 days of annual leave. This is 28 standard days, plus eight bank holidays, plus your birthday off. • Option to buy an additional 5 days per year (giving a maximum of 42 days) • Where required, 2 days per year of special leave for events that can happen in life, whether personal or family-related • Additional benefits include: • A premium performance company laptop • NHS discounts, including the Blue Light Card (as we are an NHS provider). • Equality & Diversity
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