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Lead Data Engineer - R01553055

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Lead
Posted 1 year ago
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Where you can work

Hybrid

Bengaluru, Karnataka, India

View location wording from the posting
Bangalore, Karnataka, India

Role overview

Extracted from the posting. Read the employer’s full description below.

  • GCP, Big Query, Python, Airflow, SQL, DBT

What they are looking for

  • About the Role
  • We are seeking a Senior Data Engineer with deep expertise in Google Cloud Platform (GCP) and BigQuery to lead cloud modernization initiatives, develop scalable data pipelines, and enable real-time data processing for enterprise-level systems. This is a high-impact role focused on driving the transformation of legacy infrastructure into a robust, cloud-native data ecosystem.
  • Key Responsibilities
  • 1. Data Migration & Cloud Modernization
  • Analyze legacy on-premises and hybrid cloud data warehouse environments (e.g., SQL Server).
Show all 36 items
  • Lead the migration of large-scale datasets to Google BigQuery .
  • Design and implement data migration strategies ensuring data quality , integrity , and performance .
  • 2. Data Integration & Streaming
  • Integrate data from various structured and unstructured sources, including APIs , relational databases , and IoT devices .
  • Build real-time streaming pipelines for large-scale ingestion and processing of IoT and telemetry data.
  • 3. ETL / Data Pipeline Development
  • Modernize and refactor legacy SSIS packages into cloud-native ETL pipelines .
  • Develop scalable, reliable workflows using Apache Airflow , Python , Spark , and GCP-native tools .
  • Ensure high-performance data transformation and loading into BigQuery for analytical use cases.
  • 4. Programming & Query Optimization
  • Write and optimize complex SQL queries , stored procedures, and scheduled jobs within BigQuery.
  • Develop modular , reusable transformation scripts using Python , Java , Spark , and SQL.
  • Continuously monitor and optimize query performance and cost efficiency in the cloud data environment.
  • Required Skills & Experience
  • 5+ years in Data Engineering with a strong focus on cloud and big data technologies.
  • Minimum 2+ years of hands-on experience with GCP , specifically BigQuery .
  • Proven experience migrating on-premise data systems to the cloud .
  • Strong development experience with Apache Airflow , Python , and Apache Spark .
  • Expertise in streaming data ingestion , particularly in IoT or sensor data environments.
  • Strong SQL development skills; experience with BigQuery performance tuning .
  • Solid understanding of cloud architecture , data modeling , and data warehouse design .
  • Familiarity with Git and CI/CD practices for managing data pipelines.
  • Preferred Qualifications
  • GCP Professional Data Engineer certification.
  • Experience with modern data stack tools like dbt , Kafka , or Terraform .
  • Exposure to ML pipelines , analytics engineering , or DataOps/DevOps methodologies.
  • Why Join Us?
  • Work with cutting-edge technologies in a fast-paced, collaborative environment.
  • Lead cloud transformation initiatives at scale.
  • Competitive compensation and benefits.
  • Remote flexibility and growth opportunities.

Employer description

Lead Data Engineer

Primary Skills

  • GCP, Big Query, Python, Airflow, SQL, DBT

Job requirements

  • About the Role
  • We are seeking a Senior Data Engineer with deep expertise in Google Cloud Platform (GCP) and BigQuery to lead cloud modernization initiatives, develop scalable data pipelines, and enable real-time data processing for enterprise-level systems. This is a high-impact role focused on driving the transformation of legacy infrastructure into a robust, cloud-native data ecosystem.

-

  • Key Responsibilities
  • 1. Data Migration & Cloud Modernization
  • Analyze legacy on-premises and hybrid cloud data warehouse environments (e.g., SQL Server).
  • Lead the migration of large-scale datasets to Google BigQuery.
  • Design and implement data migration strategies ensuring data quality, integrity, and performance.
  • 2. Data Integration & Streaming
  • Integrate data from various structured and unstructured sources, including APIs, relational databases, and IoT devices.
  • Build real-time streaming pipelines for large-scale ingestion and processing of IoT and telemetry data.
  • 3. ETL / Data Pipeline Development
  • Modernize and refactor legacy SSIS packages into cloud-native ETL pipelines.
  • Develop scalable, reliable workflows using Apache Airflow, Python, Spark, and GCP-native tools.
  • Ensure high-performance data transformation and loading into BigQuery for analytical use cases.
  • 4. Programming & Query Optimization
  • Write and optimize complex SQL queries, stored procedures, and scheduled jobs within BigQuery.
  • Develop modular, reusable transformation scripts using Python, Java, Spark, and SQL.
  • Continuously monitor and optimize query performance and cost efficiency in the cloud data environment.

-

  • Required Skills & Experience
  • 5+ years in Data Engineering with a strong focus on cloud and big data technologies.
  • Minimum 2+ years of hands-on experience with GCP, specifically BigQuery.
  • Proven experience migrating on-premise data systems to the cloud.
  • Strong development experience with Apache Airflow, Python, and Apache Spark.
  • Expertise in streaming data ingestion, particularly in IoT or sensor data environments.
  • Strong SQL development skills; experience with BigQuery performance tuning.
  • Solid understanding of cloud architecture, data modeling, and data warehouse design.
  • Familiarity with Git and CI/CD practices for managing data pipelines.

-

  • Preferred Qualifications
  • GCP Professional Data Engineer certification.
  • Experience with modern data stack tools like dbt, Kafka, or Terraform.
  • Exposure to ML pipelines, analytics engineering, or DataOps/DevOps methodologies.

-

  • Why Join Us?
  • Work with cutting-edge technologies in a fast-paced, collaborative environment.
  • Lead cloud transformation initiatives at scale.
  • Competitive compensation and benefits.
  • Remote flexibility and growth opportunities.
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