Advanced Data Engineer Lead

1 day ago

Bengaluru, Karnataka, India beBeeData Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Title:

A Senior Data Architect

Design and implement advanced data architectures, combining database management with full-lifecycle data engineering.

Responsibilities:

  • Lead schema design, performance tuning, ETL pipeline development, and large-scale data migrations
  • Collaborate with analytics and product teams to translate requirements into data models
  • Manage raw data storage over S3 and apply lifecycle policies
  • Optimize sql/no-sql databases, maintain petabyte-scale Elasticsearch clusters
  • Design index templates, shard/replica allocation, and rollover policies for Elasticsearch
  • Automate database maintenance tasks (vacuum, analyze) and monitor slow queries
  • Architect, build, and maintain batch and streaming ETL pipelines using EMR/Spark, Glue, Lambda, and Delta Lake
  • Lead large-scale data migrations with minimal downtime, ensuring idempotency, data quality, and rollback strategies in all migration workflows
Requirements:

  • 5+ years of hands-on experience in data modeling, ETL development, and database administration
  • Deep expertise in dimensional modeling (star/snowflake) and normalization trade-offs
  • Proven track record managing Amazon Redshift, PostgreSQL, and Elasticsearch at scale
  • Strong experience building and migrating ETL pipelines (EMR/Spark, Glue, Lambda, Delta Lake)
  • Proficiency with S3/HDFS architectures and data lake best practices
  • Excellent SQL skills and proficiency in Python or Bash scripting
  • Demonstrated success in large-scale data migrations with minimal business impact
Preferred Qualifications:

  • AWS certifications (e.g., Database – Specialty, Big Data – Specialty)
  • Experience with additional NoSQL systems (DynamoDB, Cassandra)
  • Knowledge of data mesh or data fabric architectures
  • Background in DevOps practices (CI/CD for schema and ETL code changes, Terraform/CDK)
Why Work Here:

  • Shape the backbone of our analytics and ML platforms by leading both modeling and ETL efforts
  • Influence data governance, migration strategy, and best practices across the organization
  • Competitive compensation, comprehensive benefits, and flexible work options

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