CertifyOS - Engineering Manager
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Requirements
• 10+ years of experience in software engineering, data engineering, analytics engineering, or platform engineering. • 2+ years of experience managing or leading engineering teams. • Strong hands-on background in building scalable data platforms and pipelines. • Experience with Google Cloud Platform, especially tools such as: • Cloud Composer / Airflow • Cloud Functions or Cloud Run • Strong experience with SQL and at least one programming language such as Python, Java, or Scala. • Experience with data modeling, ETL/ELT pipelines, workflow orchestration, and data warehouse design. • Strong understanding of data quality, monitoring, lineage, and governance practices. • Experience operating production data systems with SLAs and incident management. • Strong communication skills with the ability to influence across engineering, product, analytics, and business teams. • Experience with healthcare, fintech, SaaS, or other regulated data environments. • Experience with HIPAA, SOC 2, GDPR, or similar compliance frameworks. • Experience with dbt, Looker, Fivetran, Airbyte, Terraform, Kubernetes, or Docker. • Experience with real-time streaming architectures. • Experience managing cloud cost optimization for data workloads. • Experience building self-serve data platforms for analytics and business users. • Experience with master data management, data contracts, or data mesh principles. • What Success Looks Like
Responsibilities
• Team Leadership • Lead, mentor, and grow a team of data engineers. • Own hiring, onboarding, performance management, career development, and team planning. • Establish strong engineering practices around code quality, documentation, reviews, testing, observability, and incident response. • Create a culture of ownership, accountability, collaboration, and continuous improvement. • Data Platform & Architecture • Define and drive the roadmap for scalable data infrastructure on GCP. • Architect and oversee data pipelines, data models, data warehouses, and lakehouse patterns. • Ensure data systems are reliable, secure, cost-efficient, and easy to maintain. • Drive best practices around batch and streaming data processing, orchestration, monitoring, lineage, and data quality. • Delivery & Execution • Partner with product, analytics, operations, finance, and engineering teams to understand data needs and deliver high-impact solutions. • Translate business and product requirements into technical plans and execution roadmaps. • Manage project execution, sprint planning, prioritization, and delivery timelines. • Balance short-term business needs with long-term platform investments. • Data Governance, Quality & Reliability • Own data quality standards, SLAs, observability, and operational excellence for critical pipelines. • Implement governance practices around data access, privacy, compliance, lineage, and retention. • Ensure the team builds secure and compliant data systems, especially for sensitive or regulated data. • Cross-Functional Collaboration • Work closely with analytics, product engineering, infrastructure, security, and leadership teams. • Communicate technical tradeoffs, risks, and roadmap decisions clearly to technical and non-technical stakeholders. • Help define company-wide data standards, tooling, and operating models. • Build and lead a high-performing data engineering team. • Deliver reliable, scalable, and well-governed data pipelines and platforms. • Improve data availability, quality, and trust across the organization. • Enable analytics, reporting, product intelligence, and operational workflows through robust data infrastructure. • Create clear technical direction and execution discipline for the data engineering function.
Benefits
• What are your compensation expectations for this role? • Are you based in Pune or Bengaluru? • How many years of combined experience do you have in software engineering, data engineering, analytics engineering, or platform engineering? • How many years of experience do you have managing or leading engineering teams, including hiring, performance management, and career development? • Which of the following best describes your experience with Cloud Platforms (GCP. AWS, Azure)?
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