Engineering Manager - Data

We are looking for an experienced Engineering Manager - Data (GCP) to lead our data engineering function, driving the design, development, and scaling of our cloud-native data platform on Google Cloud Platform (GCP). This role combines strong technical depth in data architecture with proven people leadership and is ideal for someone who has grown from a hands-on data engineer/architect into a leader who can build and scale high-performing teams while staying close to technical decision-making.
The core responsibilities for the job include the following:
Technical Leadership:
Own the architecture, design, and roadmap of the data platform built on GCP (BigQuery, Dataflow, Pub/Sub, Cloud Composer, Dataproc, Cloud Storage, etc. ).
Drive best practices for data pipeline design, data modeling, data quality, and data governance.
Evaluate and introduce new tools, frameworks, and architectural patterns to improve scalability, reliability, and cost efficiency.
Ensure platform security, compliance, and adherence to data privacy standards.
Participate in critical design reviews, architecture decisions, and troubleshooting of complex production issues.
People and Team Management:
Lead, mentor, and grow a team of data engineers, senior engineers, and tech leads (team size: 10-25+).
Own hiring, performance management, career development, and succession planning for the team.
Foster a culture of engineering excellence, ownership, and continuous learning.
Manage team structure, capacity planning, and workload distribution across projects.
Program and Stakeholder Management:
Partner with product, analytics, data science, and business stakeholders to translate requirements into scalable data solutions.
Own delivery timelines, sprint planning, and execution using Agile/Scrum methodologies.
Manage budgets, cloud cost optimization, and vendor/tool evaluations.
Report on team KPIs, platform health, and project status to senior leadership.
Strategy:
Define and execute the long-term data engineering strategy aligned with business goals
Drive migration/modernization initiatives (e. g., on-prem to GCP, legacy pipeline re-architecture)
Contribute to org-level engineering initiatives, standards, and best practices
Requirements:
Bachelor's or master's degree in computer science, engineering, or a related field.
12-16 years of overall experience in software/data engineering, with at least 3-5 years in a people management role (managing engineers/tech leads).
Strong hands-on background in data engineering and architecture, with deep expertise in Google Cloud Platform (GCP) BigQuery, Dataflow, Pub/Sub, Cloud Composer (Airflow), Dataproc, Cloud Storage, and IAM.
Proven experience building and scaling large-scale batch and streaming data pipelines.
Strong understanding of data modeling, data warehousing, ETL/ELT design, and distributed systems.
Proficiency in SQL and at least one programming language (Python/Java/Scala).
Experience with orchestration tools (Airflow/Cloud Composer), CI/CD pipelines, and Infrastructure as Code (Terraform preferred).
Solid understanding of data governance, security, and compliance frameworks (GDPR, SOC2 etc. ).
Demonstrated experience managing stakeholders across cross-functional teams (Product, Analytics, Data Science).
Strong communication, planning, and organizational skills.
Experience with Agile/Scrum delivery frameworks.
Good to Have:
GCP certification (Professional Data Engineer / Professional Cloud Architect).
Experience with multi-cloud or hybrid-cloud data environments.
Exposure to ML/AI platform integration (Vertex AI) and MLOps.
Prior experience in a product-based or high-growth startup environment.
Experience with data mesh or modern data stack architectures.

Experience
12-16 yrs