Key Skills : Snowflake, DBT, Strong SQL and Python Job Title: Senior / Lead Snowflake Data Engineer (Contract-to-Hire) Engagement Type: 6-month contract with option to extend Work Model: Hybrid – 3 days/week on-site, 2 days remote We are seeking an experienced Snowflake Data Engineer to own the design, development, and operationalization of a modern cloud data platform that powers board-level financial dashboards (Net Revenue, EBITDA, Free Cash Flow, etc.). You will lead Snowflake environment design, write production-grade SQL, build robust dbt transformation pipelines, and contribute light-weight Python utilities that automate quality checks and CI/CD. A solid grasp of financial consolidations, inter-company eliminations, and multi-currency reporting is essential so you can partner effectively with FP&A, Accounting, and Executive stakeholders. Key Responsibilities Area What You'll Do Architecture & Modeling • Design Snowflake schemas (star, Data Vault or medallion) aligned to GAAP/IFRS reporting structures. • Translate chart-of-accounts, legal entities, and consolidation hierarchies into scalable dimensional models. Data Engineering & Transformation • Build and maintain dbt models (staging → marts) with rigorous tests, documentation, and Slim-CI. • Author complex, performance-tuned SQL (windowing, CTEs, semi-structured VARIANT) to aggregate Net Revenue, EBITDA, and Cash-Flow statements. • Implement SCD-2 and snapshot patterns for time-series finance data. Automation & Governance • Develop lightweight Python scripts (Airflow operators, Great Expectations, or custom Snowpark) for data quality, orchestration, and metadata lineage. • Enforce role-based access, masking, and tag-based governance for confidential financial data. Performance & Operations • Optimize Snowflake warehouses (clustering, caching, auto-suspend) to meet sub-second dashboard SLAs. • Establish monitoring, cost-usage analytics, and incident playbooks. Leadership & Collaboration • Mentor junior engineers, review dbt PRs, and evangelize best practices. • Partner with FP&A to interpret eliminations logic, currency conversion, and minority interest adjustments. • Present technical trade-offs and roadmap status to the Data Platform Director and CFO's staff. Minimum Qualifications 10+ years end-to-end data engineering experience, 3+ years Snowflake (enterprise scale). 4+ dbt projects in production (or 3 if each >12 months, multi-domain). Advanced SQL (analytic functions, dynamic pivots, query-profile debugging). Working Python (Snowpark, pandas) for ELT helpers and test harnesses. Proven delivery of executive-grade financial dashboards or data marts—must demonstrate understanding of eliminations, inter-company balances, multi-GAAP roll-ups. CI/CD with Git, dbt Cloud/CLI, and at least one orchestrator (Airflow, Prefect, Dagster). Cloud experience (AWS preferred: S3, IAM, Glue, Lambda or Step Functions). Strong communication skills: can brief non-technical finance leaders yet dive deep with architects. Bachelor's degree in Computer Science, Information Systems, Engineering, or Finance/Accounting; MS or MBA a plus. Preferred / Nice-to-Have Snowflake Snowpipe, Stream-&-Task, Dynamic Tables. Experience integrating SAP, Oracle E-Biz, or Workday Financials. Exposure to BI tools (Power BI, Tableau) and semantic layers (Cube, ThoughtSpot).