Manage data engineering teams to develop cloud-native data platforms, oversee projects, engage with clients, and foster team development and performance.
We are seeking Engineering Manager to lead our Data Engineering & Data & Analytics Platform Development portfolio.
This role demands a strong technical background in building data & analytics platforms, combined with proven experience in leading distributed engineering teams, managing client engagements, and driving high-quality project delivery. The ideal candidate will blend engineering depth with team leadership, delivery rigor, and client-facing capabilities.
This role demands a strong technical background in building data & analytics platforms, combined with proven experience in leading distributed engineering teams, managing client engagements, and driving high-quality project delivery. The ideal candidate will blend engineering depth with team leadership, delivery rigor, and client-facing capabilities.
Job Description:
Key Responsibilities:
Technical Leadership & Delivery Oversight:
- Lead high-performing teams of data engineers and developers to build robust, scalable data platforms and intelligent data products.
- Provide architectural guidance and support across cloud -native data engineering, including ELT pipelines, data lakes/warehouses, streaming systems, and API-first applications.
- Champion engineering excellence, modern DevOps practices, and automation across the lifecycle.
Project & Process Management:
- Own end-to-end delivery of complex data initiatives—scoping, planning, execution, and go-live—aligned with SLAs and client expectations.
- Manage multiple concurrent workstreams using Agile/Scrum or hybrid delivery methodologies.
- Track delivery KPIs (velocity, quality, cost) and ensure continuous improvement of engineering processes and execution frameworks.
People Management & Team Development:
- Conduct regular capacity planning to ensure optimal team structure as per project demands and SLA commitments.
- Define clear roles, responsibilities, and performance benchmarks for team members.
- Design and implement competency development programs, including technical upskilling, mentoring, and personalized growth paths.
- Lead hiring & staffing efforts, support candidate evaluation, and prepare shortlisted candidates for client interviews.
- Ensure smooth onboarding, project orientation, and KT for new joiners.
- Maintain regular people connects to assess motivation, understand aspirations, and proactively address attrition risk.
- Foster cross-team collaboration and knowledge sharing culture.
Client Management & Stakeholder Engagement:
- Participate in client meetings, especially during discovery, requirements gathering, and solutioning discussions.
- Contribute to effort estimation, scoping, and delivery planning for new opportunities and expansions.
- Make presentations on project status, delivery KPIs, and risk mitigation during regular cadence calls.
- Present monthly and annual performance reports to senior client and internal leadership teams.
- Act as the technical bridge between client stakeholders and internal teams, ensuring transparency, alignment, and trust.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Need to have 8+ years of hands on experience in software/data engineering background, including 5+ years in data engineering
- At least 2 years in a leadership or managerial role post the hands-on experience.
- Proven success in delivering complex, cloud-native data platforms and products at enterprise scale.
Must-Have Skills:
- Proficiency in Python, SQL, and cloud-native data engineering (preferably GCP).
- Strong hands-on experience with GCP services: BigQuery, Dataflow, Cloud Storage, Pub/Sub, Composer, GKE or any equivalent services from AWS can be considered.
- Experience designing and deploying ETL/ELT pipelines, APIs using Flask/FastAPI, and data product architectures.
- Familiar with CI/CD, Git workflows, and project management tools (e.g., Jira, Confluence).
- Experience designing and implementing AI/ML-powered applications, especially around data-driven personalization, recommendations, or predictive analytics will be highly preferred
- Understanding of MLOps practices and integration of machine learning pipelines into data engineering workflows (e.g., using Vertex AI, Kubeflow, or MLflow).
- Proven experience in project tracking, estimation, stakeholder reporting, and client-facing communications.
Nice-to-Have Skills:
- Experience in multi-region delivery teams and global stakeholder coordination.
- Exposure to data governance, compliance, or privacy frameworks (GDPR, HIPAA, etc.).
Soft Skills:
- Excellent verbal and written communication skills across all stakeholder levels.
- Strong presentation, negotiation, and relationship management capabilities.
- Empathetic leadership, with the ability to motivate, coach, and develop high-performing teams.
- Solution-oriented mindset with high ownership and accountability.
Location:
MumbaiBrand:
MerkleTime Type:
Full timeContract Type:
PermanentTop Skills
BigQuery
Ci/Cd
Cloud Storage
Composer
Confluence
Dataflow
Elt
ETL
Fastapi
Flask
GCP
Git
Gke
JIRA
Kubeflow
Mlflow
Pub/Sub
Python
SQL
Vertex Ai
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