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Blue Altair

Data-driven digital transformation and API integration

Analyst/Consultant - Data Engineer, Azure

Data EngineeringConfirmed live in the last 24 hours
Full-timePune, Maharashtra, IndiaNo salary listedIn-person

About the Job

Requirements

  • Three to five years of experience.
  • Proficiency in Python for scripting and automation tasks.
  • Experience with PySpark for large-scale data processing and transformations.
  • Expertise in designing and managing data workflows using Azure Data Factory.
  • Hands-on experience with Azure Databricks for data engineering and pipeline development.
  • Ability to manage multiple tasks and projects simultaneously.

Responsibilities

  • Design and implement data pipelines to efficiently deliver data to the Business Intelligence team.
  • Create and manage Azure Data Factory pipelines to extract data from various sources and load it into Azure Blob Storage in the bronze layer.
  • Develop pipelines using Azure Databricks to process and transform data from the bronze layer into the silver layer, creating intermediate tables.
  • Build and maintain pipelines to transform silver-layer data into gold-layer fact and dimension tables, ensuring the data is ready for analysis by the Business Intelligence team.
  • Monitor, troubleshoot, and optimize data pipelines to ensure they run smoothly and efficiently.
  • Integrate data from diverse sources, including databases, application programming interfaces, and third-party systems.
  • Develop solutions for data extraction, transformation, and loading to data warehouses or data lakes.
  • Manage and optimize relational and NoSQL databases, including SQL, MongoDB, and Cassandra.
  • Implement and maintain data models and database schemas.
  • Implement and enforce data governance policies and best practices.
  • Ensure data security and compliance with relevant regulations.

About the Company

Blue Altair

Data-driven digital transformation and API integration

Blue Altair is a technology and business consulting firm that helps clients with digital transformation by treating data as a core asset. Its offerings center on data management (data governance, metadata management, data quality), API ecosystem development and management to integrate systems and reduce duplication, and applying machine learning and responsible AI to derive insights, automate manual tasks, and optimize outcomes. The company uses automated frameworks and a digital transformation strategy that blends ML/AI tools, business analytics, and QA as a Service (QAaaS). It serves forward-thinking, agile organizations building modern cloud-based architectures (microservices, DevSecOps) to meet customer needs. Its goal is to enable organizations to capture, store, process, and analyze data effectively to improve decisions and operations.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Not listed
Founded
2015

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