Cloud-Native Data Engineering Specialist

4 days ago

Mumbai, Maharashtra, India beBeeDataEngineer Full time ₹ 15,00,000 - ₹ 25,00,000
Senior Data Engineer Position

We are seeking a skilled Senior Data Engineer to join our team. This role will involve designing, developing, and optimizing data ingestion, transformation, and governance frameworks across our data platform.

The ideal candidate will have deep expertise in cloud-native data engineering, particularly on Microsoft Azure, with familiarity with AWS and GCP. They should be proficient in SQL, PySpark, Python, and data orchestration tools, with a strong understanding of data architecture patterns such as Lakehouse and delta architecture.

Key Responsibilities:
  • Design and implement scalable, robust, and secure data pipelines using Azure Data Factory, Databricks, Synapse Analytics, and other related tools.
  • Develop and maintain ETL/ELT processes for structured and unstructured data, including change data capture, streaming pipelines, and batch ingestion.
  • Work with AWS Glue, S3, Redshift, or GCP BigQuery, Dataflow as needed, and optimize performance and cost across data workloads and cloud environments.
  • Establish and maintain data quality frameworks, observability tools, and monitoring dashboards, and define and enforce data rules, validations, anomaly detection, and reconciliation.
  • Implement data lineage and metadata tracking using Azure Purview, and drive adoption of data cataloguing, profiling, and classification tools.
  • Collaborate with data stewards and compliance teams to ensure governance alignment, and implement role-based access control (RBAC), data masking, encryption, and tokenization.
Requirements:
  • 4+ years of experience in data engineering, with at least 2+ years on Azure cloud platform.
  • Hands-on experience with Azure Data Factory, Azure Data Lake Gen2, Databricks, Synapse, Purview, and proficiency in SQL, PySpark, Python, and data orchestration tools.
  • Strong understanding of data architecture patterns, including Lakehouse and delta architecture.
  • Familiarity with Snowflake, BigQuery, Redshift, or AWS Glue, and experience with data versioning and GitOps for data.
  • Working knowledge of data observability, lineage, cataloguing, data quality, and exposure to privacy-enhancing techniques, access control, security auditing.
  • Exposure to machine learning use cases in data engineering pipelines, data quality, anomaly detection, and schema change detection.
Personal Attributes:
  • Consultative
  • Socially confident
  • Achievement oriented
  • Decisive and action oriented
  • Creative
  • Eager to learn
  • Resilient
Benefits:

This position offers the opportunity to work with cutting-edge technologies, collaborate with experienced professionals, and contribute to the development of innovative data solutions.

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