Take the lead to work closely with Product, Fundraising, Marketing and Mission stakeholders, and Project Managers to clarify project scope, elicit requirements, and identify project delivery timelines.
Own the lifecycle of data pipelines from design to production. Productionalize ad-hoc or development-level pipelines into robust, fault-tolerant automated workflows in controlled cloud environment.
Provide accountability for data engineering project delivery
Provide clear communication of project status, risks, dependencies and decision points to technology leadership and business stakeholders.
Communicate technical concepts clearly to non-technical stakeholders and bridge any gaps to ensure seamless delivery
Oversee and contribute to intake process ensuring clarity and completion of business requirements
Lead solution design and work estimation to inform and support prioritization across multiple concurrent initiatives with the Director, Data Platform & Pipeline Technology
Assign and manage execution activities across the team to ensure scope, timelines and budget are met while surfacing risks and trade-offs with recommendations
Ensure effective transition to operations post deployment or launch
Align technical decisions with business objectives and architectural standards and make technical trade-offs within standards and guardrails set by the Director.
Drive and manage technical design reviews, code reviews and solution assessments to ensure alignment with enterprise data architecture and standards
Manage technology vendors engaged in projects to ensure high quality, secure delivery that meets contractual scope, budget and timelines
Ensure vendors project work aligns with H&S standards for architecture, development, and security
Act as the primary liaison to the Analytics and Reporting team. Understand the data requirements, SLA, and downstream use cases to design optimal data models and curated data products that accelerate time to insight.
Oversee operationalization of data pipelines, ETL processes and data solutions tailored to business needs, using engineering best practices.
Ensure code and data pipeline quality through standards, peer reviews, automated testing, and CI/CD workflows.
Embed security-by-design, data privacy, and governance requirements into the development and deployment of data pipelines and platforms.
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Work with Infrastructure & Operations and Business requirements partner to identify non-functional requirements including operability, availability, performance, reliability and security
Implement rigorous data validation framework in ingestion and extraction pipelines, anomaly detection, and lineage tracking to ensure data readiness and data integrity.
Drive continuous improvement through agile ceremonies including sprint planning and retrospectives
Ensure technical documentation is completed/updated for all delivered solutions.
Support team with issue management escalation (level 3) and drive continuous improvement.
Establish robust logging, alerting, and monitoring mechanism for all production ETL jobs to minimize downtime and resolve data delivery delays.
Lead, mentor, and coach a team of data engineers, data analysts and business system analysts.
Facilitate professional development, including continuous feedback, skills growth, and performance management.
Help foster a collaborative, high‑performing engineering culture rooted in ownership, accountability, and delivery excellence.
Foster collaboration with cross-functional partners in Product, Business, Data and Application Engineering, Security, and Infrastructure & Operations.
Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline, or an equivalent combination of education and progressive professional experience.
Minimum of 5+ years of technical leadership experience managing teams of engineers and analysts including coaching and driving delivery accountability
8 – 10+ years of data engineering and technical solution design
Experience with Azure and first party data services (e.g. Data Factory, Fabric, Azure Databricks), data integration via APIs, and modern data engineering frameworks (e.g., Python, SQL)
Experience with data lakehouse architectures, Medallion design principle, and ETL/ELT job operationalization deployment process.
Experience with project stakeholder management and the ability to translate business requirements into technical solutions
Expert-level knowledge of data warehousing concept, schema design (Star/Snowflake).
Advanced proficiency with ETL transformation framework libraries (PySpark, Spark)
Practical knowledge of cloud platforms (Azure preferred, or GCP).
Experience with CI/CD pipelines, automated testing, Git-based workflows, and Agile delivery.
Data solution design, implementation, and troubleshooting
Custom data engineering, operations and reliability management
Business requirements translation into technical solutions
Stakeholder communication and collaboration
Team management and hands-on technical and requirements gathering coaching
Vendor coordination and delivery oversight
Solution estimation and budget management skills – engineering project execution.
Ability to work in a fast paced, agile and multiple stakeholder environment
Ability to prioritize and work on multiple tasks across multiple stakeholders
Ability to work with cross functional teams to see a project to successful completion
Strong understanding of software development environments and databases
Strong analytical skills in data diagnostics, issue isolation and troubleshooting
Comfortable facilitating conversations with different stakeholders, presenting technical concepts to non-technical audiences
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