zoho_recruit
Head of Data & Analytics
Parkar Digital
Pune, IND
Full-time
Senior · 18+ years experience
Onsite
Discovered 3 weeks ago
BigQueryDataflowDatabricksDelta LakeApache IcebergSnowflake
Free
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Role Overview
We are seeking a visionary and hands-on Senior Leader in Data Engineering to lead the design, development, and scaling of our enterprise data ecosystem.
The ideal candidate will possess a deep understanding of cloud-native architecture, modern data platforms, and real-time processing frameworks, while also demonstrating leadership acumen to scale high-performing teams and drive data strategy across the enterprise.
Key Skills for This Role
BigQueryDataflowDatabricksDelta LakeApache IcebergSnowflake
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Technology Stack & Requirements
- Cloud & Storage:
- AWS (Glue, Redshift, S3), Azure (Synapse, Data Factory), GCP (BigQuery, Dataflow).
- Lakehouse architectures (Databricks, Delta Lake, Apache Iceberg, Snowflake).
- Data Processing & Orchestration: Apache Spark, PySpark, Kafka, Flink, Airflow, DBT, Dagster.
- Data Integration & Pipelines: Informatica, Talend, Fivetran, Matillion.
- Programming & Tools:
- Python, SQL, Scala.
- CI/CD (GitHub Actions, Jenkins), Infrastructure as Code (Terraform, CloudFormation).
- Data Governance & Quality: Collibra, Alation, Monte Carlo, Great Expectations, DataDog for observability.
- AI/ML Integration Readiness: Exposure to MLOps pipelines and integration with ML platforms (SageMaker, Vertex AI, Azure ML).
- Proven experience building enterprise-scale data platforms (multi terabyte/petabyte scale).
- Expertise in data architecture design, platform modernization, and cloud migration.
- Leadership experience in managing global teams and working in agile environments.
- Deep understanding of data compliance and governance (GDPR, HIPAA, SOC2).
- Strong communication and stakeholder management skills, especially with non technical audiences.
- Delivery Responsibility: The Head of Data & Analytics will need to have hands-on delivery ownership, ensuring that data engineering initiatives are executed with precision, on time, and within scope.
- Own end-to-end delivery of enterprise data platform projects, from requirements through production deployment, ensuring adherence to timelines, budgets, and quality standards.
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