Job Summary

We are seeking an experienced Data Services Delivery (DSD) Leader to own the end-to-end delivery of data services, spanning both Application/Data Development and Production Support. This is a hybrid technical-managerial role for a leader who can balance hands-on technical credibility with large-scale program leadership. The ideal candidate has successfully run large, complex data programs, managed distributed delivery teams, and driven operational excellence across the full data lifecycle ‚from build to run.

Key Responsibilities

End-to-End Delivery Ownership

1. Own and drive end-to-end data services delivery, covering both new development/enhancements and L1/L2/L3 production support for data platforms, pipelines, and integrations.
2. Act as the single point of accountability for delivery commitments, SLAs, and quality across the data services portfolio.
3. Define and implement delivery governance, ensuring predictable, high-quality outcomes across multiple concurrent workstreams.
4. Farming existing accounts for AI and Data Opportunities and improving repeat business value at account level for Data & AI opportunities.

Program & Stakeholder Leadership

1. Lead large, cross-functional data programs involving multiple teams, vendors, and stakeholders across geographies.
2. Partner with business, product, and engineering leadership to translate strategic priorities into delivery roadmaps.
3. Manage program-level risk, budget, resourcing, and executive reporting/status updates.

Technical Leadership

1. Provide hands-on technical direction on data architecture, pipeline design, data quality frameworks, and modern data platforms (cloud data warehouses, ETL/ELT, orchestration tools, etc.).
2. Review and guide technical design decisions; ensure engineering best practices, scalability, and cost-efficiency.
3. Stay close enough to the technology to credibly engage in architecture discussions, troubleshoot escalations, and mentor technical teams.
4. Participate in technical solutioning for AI and Data opportunities, Solutions and Accelerators

Support Operations Management

1. Own production support operations for data platforms ‚incident management, root cause analysis, problem management, and continuous service improvement.
2. Establish and monitor SLAs/OLAs, KPIs, and dashboards for support performance (MTTR, ticket volume, recurring issues, etc.).
3. Drive automation and self-healing initiatives to reduce manual support effort and improve system reliability.

Team Leadership & Development

1. Build, lead, and mentor a team of technical leads, developers, and support engineers across development and support functions.
2. Foster a culture of ownership, continuous improvement, and technical excellence.
3. Manage staffing, performance, and capacity planning across development and support pods.

Process & Governance

1. Implement and mature delivery frameworks (Agile/Scrum, ITIL, DevOps/DataOps practices) suited to a dual development + support model.
2. Drive continuous improvement in delivery processes, tooling, and documentation.
3. Ensure compliance with data governance, security, and regulatory requirements.

Skill Requirements

1. 15+ years of overall experience in data engineering/technology delivery, with 5+ years in a leadership role managing delivery and/or support teams.
2. Proven experience leading large, complex data programs end-to-end (multi-team, multi-vendor, cross-geography).
3. Strong technical background in data engineering ‚hands-on or recent hands-on experience with:
1. Data pipelines/ETL-ELT tools (e.g., Informatica, Talend, dbt, Airflow, ADF)
2. Cloud data platforms (e.g., Snowflake, Databricks, AWS Redshift, Azure Synapse, GCP BigQuery)
3. SQL and at least one programming language (Python, Scala, Java)
4. Data Governance, Data Management Services, Data modeling, Warehousing, and Integration Concepts
4. Demonstrated experience owning both delivery/development and production support functions.
5. Strong experience with ITIL-based support models, incident/problem management, and SLA governance.
6. Excellent stakeholder management skills ‚comfortable engaging with senior business and technology leadership.
7. Experience with Agile/Scrum and DevOps/DataOps delivery practices.
8. Strong people leadership experience ‚managing, mentoring, and growing technical teams (typically 20 - 1000+ FTEs, including onshore/offshore models).

Preferred Qualifications

1. Experience in managed services / global delivery / shared services environment.
2. Exposure to data governance, data quality, and metadata management frameworks
3. Relevant certifications (PMP, SAFe, ITIL, cloud platform certifications).
4. Experience with FinOps/cost optimization for cloud data platforms.
5. Prior experience in [Insert relevant industry, e.g., Banking, Healthcare, Retail].

Key Attributes

1. Technical credibility ‚can go deep enough to challenge architecture and troubleshoot with the team, not just manage from a distance.
2. Execution-focused ‚track record of delivering large programs on time, on budget, and at quality.
3. Balances build and run ‚equally comfortable driving new development and stabilizing/operating live systems.
4. Strong communicator ‚able to translate technical complexity into business impact for senior stakeholders.
5. Calm under pressure ‚experienced in managing production incidents and escalations without losing sight of long-term delivery goals.

Other Requirements

1. Strong technical background in data engineering ‚hands-on or recent hands-on experience with:
1. Data pipelines/ETL-ELT tools (e.g., Informatica, Talend, dbt, Airflow, ADF)
2. Cloud data platforms (e.g., Snowflake, Databricks, AWS Redshift, Azure Synapse, GCP BigQuery)
3. SQL and at least one programming language (Python, Scala, Java)
4. Data Governance, Data Management Services, Data modeling, Warehousing, and Integration Concepts.