Azure Data Engineer-Technical Lead

Kindly find the Job Description Below.

Job Title : Technical Lead-Azure Data Engineer

Location : Bangalore

Years of Experience : 10+ years of experience

Sigmoid works with a variety of clients from start-ups to fortune 500 companies. We are looking for a detailed oriented self-starter to assist our engineering and analytics teams in various roles as a Software Development Engineer.

As an Technical Lead- Data Engineer, you will be responsible for building a highly-scalable and extensible big data platform that provides the foundation for collecting, storing, modeling, and analyzing massive data sets from multiple channels.

We are looking for a skilled Data Engineer with 10+ years of experience in big data technologies, particularly Azure, Python, PYSpark, SQL and data lakehouse architectures. The ideal candidate will have a strong background in building scalable data pipelines and experience with modern data storage formats, including Apache Iceberg. You will work closely with cross-functional teams to design and implement efficient data solutions in a cloud-based environment.

Key Responsibilities :

Data Pipeline Development :

Design, build, and optimize scalable data pipelines using Apache Spark.

Implement and manage large-scale data processing solutions across data lakehouses.

Data Lakehouse Management :

Work with modern data lakehouse platforms (e.g.Apache Iceberg) to handle large datasets.

Optimize data storage, partitioning, and versioning to ensure efficient access and querying.

SQL & Data Management :

Write complex SQL queries to extract, manipulate, and transform data.

Develop performance-optimized queries for analytical and reporting purposes.

Data Integration :

Integrate various structured and unstructured data sources into the lakehouse environment.

Work with stakeholders to define data needs and ensure data is available for downstream consumption.

Data Governance and Quality :

Implement data quality checks and ensure the reliability and accuracy of data.

Contribute to metadata management and data cataloging efforts.

Performance Tuning :

Monitor and optimize the performance of Spark jobs, SQL queries, and overall data infrastructure.

Work with cloud infrastructure teams to optimize costs and scale as needed.

Qualifications :

Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.

9+ years of experience in data engineering, with a focus on Java / python, Spark and SQL Programming languages.

Hands-on experience with Apache Iceberg, Snowflake, or similar technologies.

Strong understanding of data lakehouse architectures and data warehousing principles.

Proficiency in AWS data services.

Experience with version control systems like Git and CI / CD pipelines.

Excellent problem-solving and analytical skills.

Strong communication and collaboration skills.

Nice to Have :

Experience with containerization (Docker, Kubernetes) and orchestration tools like Airflow.

Certifications in Azure cloud technologies