Description

You will build scalable data pipelines and architect modern data environments to support advanced analytics.

Responsibilities

• Design and implement data models for data warehousing and semantic models.
• Engineer ETL/ELT pipelines using big data technologies like Hive and Spark.
• Establish data standards, lineage, and technical glossaries from pipelines to catalog tools.
• Manage data orchestration and implement DataOps and Data Observability practices.
• Analyze SQL, Python, and ETL/ELT transformation scripts to ensure data quality.

Required Skills

• 10+ years of data engineering experience including pipeline execution and scripting.
• 5+ years of proven data architecture experience with a focus on data warehousing.
• 5+ years of hands-on experience with data modeling best practices.
• Strong DBA background with architect-level experience.
• Proficiency in Python or Java.
• Expertise in SQL and ETL/ELT processes.
• Experience with data orchestration tools such as Apache Airflow or Ctrl-M.
• Experience with modern data architectures including Snowflake and Azure.
• Working knowledge of reporting tools like MicroStrategy or Power BI.

Preferred Skills

• Experience with StreamSets and dbt.
• Hands-on experience with Starburst and DataOps.

Key Skills

Education

Not specified