Data Engineering Manager - Semantic Layer

Title: Data Engineering Manager - Semantic Layer

Location: Local to Dallas, TX. Office is in Coppell, TX 4 days a week

Video Interview

Job Description 

Must have strong Snowflake. Will need to work onsite 4x a week for at least the first 6 weeks

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.