Sr Data Engineer
Phoenix, NM - USA
Job Summary
Job Description
Role - Sr Data Engineer
Experience Required - 6 Years
Must Have Technical/Functional Skills
Strong hands-on experience in Big Data technologies and distributed data processing frameworks.
Proficiency in Python for data engineering scripting and performance optimization.
Extensive experience with Apache Spark (PySpark/Spark SQL) for large-scale data transformation and processing.
Solid experience in designing and developing ETL/ELT pipelines for batch and real-time data processing.
Experience working with Google Cloud Platform (GCP) services such as BigQuery Cloud Storage Dataflow Dataproc Composer and Pub/Sub.
Strong understanding of data warehousing concepts dimensional modeling and data lake architectures.
Experience with CI/CD pipelines and DevOps practices for data engineering workflows.
Proficiency in version control systems (Git) and build/release management.
Experience with workflow orchestration tools such as Apache Airflow or Cloud Composer.
Experience working in Agile/Scrum environments with cross-functional teams.
Strong analytical and problem-solving skills
Strong collaboration and stakeholder communication skills
Roles & Responsibilities
Design develop and maintain scalable Big Data pipelines using Spark (PySpark/Spark SQL) for batch and real-time processing.
Build and optimize robust ETL/ELT workflows to ingest transform and load data from multiple structured and unstructured sources.
Develop high-performance SQL queries and implement efficient data models to support analytics and reporting needs.
Architect and implement data solutions on Google Cloud Platform (GCP) using services such as BigQuery Dataproc Dataflow Cloud Storage Pub/Sub and Composer.
Monitor troubleshoot and resolve production issues in distributed and cloud environments.
Automate operational processes and enforce coding standards version control and documentation practices.
Automate operational processes and enforce coding standards version control and documentation practices.
Collaborate with cross-functional teams including business stakeholders data engineers and product teams
Drive analytics initiatives to provide actionable insights.
Participate in Agile ceremonies including sprint planning design reviews and retrospectives.
Continuously improve reporting frameworks and data processes in alignment with Agile delivery practices