Senior Azure Data Engineer/Azure Data Engineering - Architect

LOCATION- CHENNAI/HYDERABAD (HYBRID)

Our client is a 4-year-old, fast growing, "Great Place to work" certified, Software and Services company with a growing team of 200+ professionals working across various cities in India and US.

Mission: They will build simple, scalable solutions using Blockchain, IoT and AI Technologies that enable their customers to realize unprecedented business value year after year.

Vision: They will become an advanced information technology company powered by happy, intellectual and extraordinarily capable people.

Roles and Responsibilities:

Designs, develops, optimizes, and maintains data architecture and pipelines that adhere to Data Pipeline (ELT) principles and business goals.

Solves complex data problems to deliver insights that help the business achieve its goals.

Creates data products for engineers, analysts, and data scientist team members to accelerate their productivity.

Engineers effective features for modeling in close collaboration with data scientists and businesses.

Leads the evaluation, implementation, and deployment of emerging tools and processes for analytics data engineering to improve productivity and quality.

Partners with machine learning engineers, BI, and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.

Requirements

Bachelor's degree in computer science, statistics, engineering, or a related field.

8-15 years of experience required.

Experience in PySpark is required for this position, with strong knowledge of Microsoft Fabric being a plus.

Experience designing and maintaining data warehouses and/or data lakes with big data technologies such as Spark/Databricks or distributed databases like Redshift and Snowflake .

Experience in housing, accessing, and transforming data in various relational databases.

Experience building data pipelines and deploying/maintaining them following modern Data Engineering best practices (e.g. , DBT, Airflow, Spark, Python OSS Data Ecosystem ).

Knowledge of Software Engineering fundamentals and software development tooling (e.g., Git, CI/CD, JIRA ), with familiarity with the Linux operating system and the Bash/Z shell.

Experience with cloud database technologies (e.g., Azure ) and developing solutions on cloud computing services and infrastructure in the data and analytics space.

Basic familiarity with BI tools (e.g., Alteryx, Tableau, Power BI, Looker).

Expertise in ELT and data analysis, primarily SQL.

Conceptual knowledge of data and analytics, such as dimensional modeling, reporting tools, data governance, and structured and unstructured data.