Data Engineering Specialist

2 days ago

Kollam, Kerala, India beBeeDataEngineering Full time ₹ 1,20,00,000 - ₹ 2,40,00,000
Job Opportunity

We seek a seasoned professional to fill the role of Data Engineering Specialist.

This position involves designing and developing scalable enterprise data analytics solutions, from source system through ingestion and reporting.

  • Data Pipeline Development:

Data engineers are responsible for crafting robust, scalable, and high-quality data pipelines that support analytics and reporting needs. This entails:

  • Integration of structured and unstructured data from various sources into data lakes and warehouses.
  • Creation and maintenance of scalable ETL/ELT pipelines for batch and streaming data using Azure Data Factory, Databricks, Snowflake, and Azure SQL Server.
  • Collaboration with data scientists, analysts, and platform engineers to enable analytics and machine learning use cases.
  • Design, development, and optimization of DBT models to support scalable data transformations.
  • Cloud Platform Expertise:

The ideal candidate will operationalize data solutions on cloud platforms, integrating services like Azure, Snowflake, and third-party technologies.

  • Management of environments, performance tuning, and configuration for cloud-native data solutions.
  • Data Modeling & Architecture:

Applying dimensional modeling, star schemas, and data warehousing techniques to support business intelligence and machine learning workflows.

  • Collaboration with solution architects and analysts to ensure models meet business needs.
  • Data Governance & Security:

Ensuring data integrity, privacy, and compliance through governance practices and secure schema design.

  • Implementation of data masking, access controls, and metadata management for sensitive datasets.
  • Cross-Functional Collaboration & Agile Delivery:

Working closely with cross-functional teams, including product owners, architects, and business stakeholders to translate requirements into technical solutions.

  • Participation in Agile ceremonies, sprint planning, and DevOps practices for continuous integration and deployment.

Key Requirements:

  • 7+ years of experience in data engineering or design, designing, developing, and deploying scalable enterprise data analytics solutions.
  • 5+ years of experience in machine learning lifecycle using Azure Kubernetes service, Azure Container Instance service, Azure Data Factory, Azure Monitor, Azure DataBricks building datasets, ML pipelines, experiments, logging, and monitoring.
  • 5+ years of experience in data engineering using Snowflake.
  • Proficiency in SQL and one other programming language (e.g., R, Python, C++, Minitab, SAS, Matlab, VBA).
  • Strong experience with cloud platforms (AWS, Azure) and containerization technologies (Docker, Kubernetes).
  • Experience with CI/CD tools (GitHub Actions, GitLab, Jenkins) and security best practices in DevOps and ML Ops.
  • Familiarity with API development (e.g., REST).
  • Agile/Scrum operating experience using Azure DevOps.
  • Experience with MS Cloud - ML Azure Databricks, Data Factory, Synapse, among others.

Qualifications:

  • A degree is not required; focus is on the right skillset and commitment to assigned work/projects.
  • Two rounds of interviews for this position.

This role involves close collaboration with cross-functional teams to enable analytics and ML use cases.

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