Data Engineering Manager - Semantic Layer

Data Engineering Manager - Semantic Layer Location: Local to Dallas, TX. Office is in Coppell, TX 4 days a week (Look for local) Duration: 9+ Months Contract MoI: Video Interview Will need to work onsite 4x a week for at least the first 6 weeks Job Description Must have strong Snowflake. They are open to someone more junior or senior - just need to have very strong executive presence and hands on experience with Snowflake and Semantic layer. Kafka is a big plus. Here are some additional details for this role - looking for someone very strong on the Data side who has also been a program manager more recently. Looking for local candidates ASAP. Resumes need to highlight semantic/reporting & analytics/visualization. Also looking for reporting tool experience and ideally technical/project management certifications. Updated description: This role will provide hands‑on delivery leadership, technical oversight, and risk management to ensure engineering milestones are met, risks are addressed, and assets are delivered on time and to specification. The Manager will own: Semantic Views & Reporting Enablement business‑focused track driving configuration of semantic layers, reporting views, and dashboard readiness for downstream consumers. Key Responsibilities Serve as the delivery lead for one of the core data engineering tracks (Semantic layer/reporting). Ensure all engineering deliverables are executed against the program roadmap and timelines; identify risks and implement mitigation strategies. Work daily with Deloitte engineering teams, internal program managers, AVPs, and business stakeholders to track progress and resolve issues. Attend and contribute to daily scrums with onshore, offshore, and Deloitte engineers, ensuring blockers are removed and deliverables stay on track. Provide technical oversight for data engineering efforts including: Snowflake pipelines (Bronze, Silver layers) DBT transformations and configuration Semantic view modeling for BI/reporting Testing frameworks and validation processes Mentor and monitor engineers across the workstream; foster accountability and quality delivery. Deliver polished status updates and risk reports to program managers and executive leadership (CIO, AVPs, executive steering committee). Collaborate with PMO program managers, ensuring alignment across business, change management, Deloitte, and cloud vendors (Google, AWS, etc.). Act as the bridge between engineering execution and program leadership, ensuring clarity in priorities, milestones, and dependencies. Qualifications 6+ years of experience in data engineering and delivery leadership. Proven track record managing delivery of Snowflake-based data platforms (pipelines, ETL, semantic layers). Hands‑on experience with: SQL, Python, PySpark Snowflake (data modeling, performance optimization, RBAC, Bronze/Silver/Gold architecture) DBT for transformations/configurations ETL/ELT tools (Airflow, Informatica, Glue, ADF, etc.) Strong background in data pipeline testing, validation, and quality frameworks. Experience working with consulting partners (Deloitte preferred) and distributed onshore/offshore engineering teams. Excellent delivery and risk management skills able to foresee challenges, maintain RAID logs, and keep workstreams accountable. Strong executive presence; comfortable reporting to AVPs, CIO, and executive steering committees. Effective communicator who can bridge business and technical discussions. Experience in financial services, mortgage, or other highly regulated industries preferred. Reporting Structure These roles will report directly to an AVP or Noble, depending on alignment within the program's data platform leadership structure. Program Managers from the PMO will oversee the broader portfolio, while Data Engineering Managers own track‑level delivery. #J-18808-Ljbffr Intersources