Job Title: Technical Project Manager – Data Engineering (Databricks Practice)
Company: V4C.ai
Type: Full-time
Experience Level: Mid to Senior
Key ResponsibilitiesLead and manage end-to-end delivery of data engineering projects, ensuring timelines, budgets, and quality standards are met.
Coordinate between data engineers, solution architects, business stakeholders, and clients to align project objectives.
Track and manage project plans, risks, dependencies, and progress through agile/scrum methodologies.
Ensure adherence to data engineering best practices across design, build, and deployment.
Support solution design discussions for data pipelines, data lake/lakehouse, and cloud data platforms.
Drive continuous improvement by implementing accelerators, reusable assets, and governance frameworks.
Partner with the Technology Steering Committee to stay updated on emerging trends, tools, and practices.
Prepare and deliver regular project status updates, executive reports, and stakeholder communication.
Experience: 5+ years in project/program management with strong exposure to data engineering or analytics projects.
Technical Knowledge (preferred, not mandatory):
Familiarity with Databricks, Apache Spark, or other big data frameworks.
Understanding of cloud platforms (AWS, Azure, or GCP).
Exposure to data lakes, data warehouses, and lakehouse concepts.
Knowledge of CI/CD pipelines, version control, and agile delivery practices.
Soft Skills:
Excellent leadership, communication, and stakeholder management skills.
Strong problem-solving and conflict-resolution abilities.
Proven ability to manage distributed, cross-functional teams.
Prior experience managing projects with Databricks or modern data platforms.
Project management certifications (PMP, CSM, PRINCE2, or equivalent).
Familiarity with monitoring and observability tools (Datadog, Prometheus, etc.).
Exposure to ML or advanced analytics projects.