Senior Azure Data Engineer
Description For Senior Azure Data Engineer
Qode is seeking a Senior Azure Data Engineer to join their team in a hybrid work environment. This role requires 8-10 years of experience and focuses on designing, developing, and maintaining data architecture and pipelines. The ideal candidate will have expertise in PySpark, big data technologies, and cloud database solutions, particularly Azure. They will be responsible for solving complex data problems, creating data products, and collaborating with data scientists and business teams. The position demands strong skills in ELT, data analysis, and modern data engineering practices, as well as familiarity with software engineering tools and BI platforms. This is an excellent opportunity for a seasoned data engineer to make a significant impact on strategic enterprise projects and initiatives.
Responsibilities For Senior Azure Data Engineer
- 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 For Senior Azure Data Engineer
- Bachelor's degree in computer science, statistics, engineering, or a related field
- 8-10 years of experience required
- Experience in PySpark
- Strong knowledge of Microsoft Fabric (preferred)
- 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)
- 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
