Technical Lead - Data Engineering

Description :

We are looking for a skilled Data Engineer with 9+ 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 Design, build, and optimise scalable data pipelines using Apache Spark.

• Implement and manage large-scale data processing solutions across data lakehouses.
• Work with modern data lakehouse platforms (e. g. Apache Iceberg) to handle large datasets.
• Optimise data storage, partitioning, and versioning to ensure efficient access and querying.
• Write complex SQL queries to extract, manipulate, and transform data.
• Develop performance-optimised queries for analytical and reporting purposes.
• 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.
• Implement data quality checks and ensure the reliability and accuracy of data.
• Contribute to metadata management and data cataloguing efforts.
• Monitor and optimise the performance of Spark jobs, SQL queries, and overall data infrastructure.
• Work with cloud infrastructure teams to optimise costs and scale as 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 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.
• Experience with version control systems like Git and CI / CD pipelines.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.
• Experience with containerization (Docker, Kubernetes) and orchestration tools like Airflow.
• Certifications in Azure cloud technologies.

(ref : hirist.tech)