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.
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.
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