Senior Data Infrastructure Specialist

2 days ago

Bengaluru, Karnataka, India beBeeDataEngineer Full time US$ 1,04,000 - US$ 1,30,878

We are seeking a seasoned professional to spearhead the design and implementation of scalable data pipelines that serve the needs of diverse stakeholders.

You will make a significant impact by

  • Developing, maintaining, and refining data pipelines to meet the evolving needs of multiple teams including software developers, data scientists, analysts, and business units.
  • Ensuring data pipelines are modular, resilient, and optimized for performance and low maintenance.
  • Collaborating with AI/ML teams to support training, inference, and monitoring needs through structured data delivery.
  • Implementing ETL/ELT workflows for structured, semi-structured, and unstructured data using cloud-native tools.
  • Working with large-scale data lakes, streaming platforms, and batch processing systems to ingest and transform data.
  • Establishing robust data validation, logging, and monitoring strategies to maintain data quality and lineage.
  • Optimizing data infrastructure for scalability, cost-efficiency, and observability in cloud-based environments.
  • Maintaining compliance with governance policies and data access controls across projects.
Requirements

To succeed in this role, you must possess:

  • Bachelor's degree in Computer Science, Information Systems, or a related field.
  • 4+ years of experience designing and deploying scalable data pipelines in cloud environments.
  • Proficiency in Python, SQL, and data manipulation tools and frameworks (e.g., Apache Airflow, Spark, dbt, Pandas).
  • Practical experience with data lakes, data warehouses (e.g., Redshift, Snowflake, BigQuery), and streaming platforms (e.g., Kafka, Kinesis).
  • Strong understanding of data modeling, schema design, and data transformation patterns.
  • Experience working with AWS (Glue, S3, Redshift, Sagemaker) or Azure (Data Factory, Azure ML Studio, Azure Storage).
  • Familiarity with CI/CD for data pipelines and infrastructure-as-code (e.g., Terraform, CloudFormation).
  • Exposure to building data solutions that serve AI/ML pipelines, including feature stores and real-time data ingestion.
  • Familiarity with observability, data versioning, and pipeline testing tools.
  • Ability to engage with diverse stakeholders, gather data requirements, and support iterative development cycles.
  • Background or familiarity with the Power, Energy, or Electrification sector is a strong plus.
  • Knowledge of security best practices and data compliance policies for enterprise-grade systems.

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