Data Engineer

About the role

We are hiring a mid-level Data Engineer to build and own the pipelines, models, and user-facing data products that power private markets investing at DigitalBridge. You will work in the middle of the stack — Snowflake, dbt, and Airflow — turning raw operator, fund, deal, and portfolio data into governed, high-trust datasets that investment, portfolio operations, finance, and IR teams actually use. This is a builder role with real business proximity: you'll sit close to the domains you serve, translate their questions into models, and make sure our data investments show up as measurable decision value.

What you'll do

• Design, build, and operate production data pipelines in Snowflake + dbt + Airflow, from ingest through curated marts to consumption.

• Model private markets data — funds, vehicles, LPs, GPs, portfolio companies/assets, deals, cash flows, valuations, KPIs, ESG — into clean, well-documented dimensional and semantic layers.

• Partner directly with investment, portfolio operations, finance, and IR stakeholders to understand decisions, align on definitions, and ship datasets that answer their real questions.

• Own the metadata and discovery experience in our data catalog (definitions, ownership, lineage, freshness, certification) so users can find and trust what they need without asking an engineer.

• Build user-facing data products — curated marts, semantic views, notebooks, and app-backing endpoints — with a bar for usability, documentation, and reliability.

• Drive measurable value out of our data investments: instrument usage, retire low-value pipelines, and prioritize work against dollar-weighted stakeholder impact.

• Implement data quality, testing, freshness SLAs, and observability (dbt tests, Great Expectations / Elementary or equivalent, Airflow alerting).

• Contribute to governance: sensitivity classification, access patterns, row/column-level security in Snowflake, and lineage/audit posture for regulated workflows.

• Collaborate with the DataBridge / platform team on semantic access, MCP-fronted endpoints, and AI-ready datasets.

Required experience

• 3–6 years building production data pipelines and models in a modern cloud data stack.

• Strong hands-on Snowflake (warehouses, RBAC, Streams/Tasks, Snowpipe, cost/perf tuning), dbt (models, tests, macros, exposures, docs), and Airflow (DAG design, sensors, retries, SLA management).

• Advanced SQL and solid Python for ingestion, testing, and light service work.

• Deep private markets data experience — funds, capital calls/distributions, NAV/valuations, portfolio company financials/KPIs, waterfalls, GP/LP structures, or infrastructure/real assets data.

• Demonstrated business ↔ data alignment: taking a stakeholder question, negotiating definitions, modeling, and delivering a used, trusted dataset.

• Experience implementing and maintaining a data catalog (Atlan, Collibra, Alation, Select Star, or dbt-native) with real ownership of metadata quality.

• Track record shipping user-facing data products (BI marts, semantic layers, embedded data in apps).

• A value-driven mindset: comfortable measuring adoption, retiring dead pipelines, and reporting outcomes not activity.

Nice to have

• Experience in a private equity, private credit, infrastructure, or real estate manager; or with fund administrators (Citco, SS&C, Alter Domus).

• Familiarity with common private markets sources: Preqin, PitchBook, MSCI, iLEVEL, eFront, Allvue, Investran, Aladdin.

• Exposure to semantic layers / metrics stores (Cube, dbt Semantic Layer, LookML) and BI (Tableau, Power BI, Sigma).

• Experience wiring datasets into agentic / LLM workflows (MCP, RAG, tool-calling) with governance controls.

• Comfort with Terraform for Snowflake/Airflow infra as code.

At DigitalBridge, we strive to create an inclusive environment where diverse employees want to work and where they can flourish professionally. In furtherance of our culture, all qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law.