Senior Data Lead

5 hours ago

Hyderabad, Telangana, India Loyalty Methods Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Position: Senior Data Lead / Data & Analytics Manager Product Engineering

Location: Hyderabad

Experience: 12+ years

Employment Type: Full-Time

Role Overview:

We are seeking a hands-on Senior Data & Analytics Manager to lead enterprise-scale data engineering and advanced analytics initiatives. The role combines expertise in cloud and on-prem data platforms with AI/ML and BI-driven analytics to drive measurable business outcomes. The ideal candidate will lead distributed teams, design scalable data solutions, and partner closely with product engineering teams to power data-informed product features, personalization, and experimentation strategies.

Key Responsibilities:

  • Lead, mentor, and grow a high-performing data engineering and analytics team, driving strategic direction, delivery excellence, and professional development.
  • Design, implement, and optimize modern ETL pipelines and data warehouses (AWS, Azure, Snowflake, Redshift, Databricks, etc.).
  • Develop and execute advanced analytics and predictive modeling solutions (e.g., churn, sales uplift) leveraging AI/ML workflows.
  • Collaborate with product teams to define data requirements, instrumentation, and telemetry for product insights.
  • Translate complex data findings into actionable insights and communicate recommendations effectively to technical and non-technical stakeholders.
  • Implement monitoring, observability, and CI/CD practices to ensure resilience and reliability of data pipelines.
  • Drive cost-efficient, secure, and scalable data solutions while ensuring governance, data quality, and operational reliability.

Required Skills & Expertise:

  • Cloud Platforms: AWS (Glue, Redshift, DMS, S3, EMR), Azure (ADF, Synapse, Databricks)
  • ETL/Data Integration Tools: PDI, Airflow, Real-Time/Near Real-Time ETL Tools
  • Programming & Scripting: Python, PySpark, Scala, SQL/PLSQL, Unix/Shell scripting
  • Databases & Warehousing: Redshift, Snowflake, Teradata, Oracle, Postgres, AuroraDB, MongoDB, HBase
  • BI & Analytics Tools: Power BI, Quicksight
  • Advanced Analytics: Statistical modelling, machine learning, AI/ML applications, experimentation/AB testing methods

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