Job Summary Are you an exceptional
Data Engineer (Analytics Focus) with a passion for building robust data solutions and optimizing performance? Do you thrive in a collaborative environment and have a strong knack for translating data requirements into efficient designs? Are you analytical and curious? If you're excited about being part of a world-class Data Science team that specializes in inbound data and are skilled in Python, SQL, Apache Spark, data architecture, and more, we want to hear from you.
Key Responsibilities - Collaborate with data scientists and analysts to understand their data needs and create data solutions that support their analytical and reporting requirements
- Design and implement efficient and scalable ETL processes to move and transform data from source systems to data warehouses or data lakes
- Develop and maintain data pipelines to efficiently ingest, process, and transform data from diverse sources
- Utilize your expertise in Python and SQL to manipulate and analyze large datasets, ensuring data quality and accuracy
- Leverage your intimate knowledge of Apache Spark to optimize data structures and processing performance, contributing to enhanced data processing capabilities
- Collaborate closely with data teams to understand source applications and stored data structures to translate them into effective enterprise data architecture and design
- Serve as a data architect, designing and implementing solutions that align with business objectives and data strategy
- Exploratory Data Analysis to inform design decisions of data assets
- Work with various APIs to extract data from external sources and integrate it seamlessly into our data ecosystem
- Demonstrate your proficiency in automating data pipelines, using Azure Synapse and Data Factory to streamline data workflows
- Apply your skills in relational modeling to design and maintain data models that support reporting and analytics needs
- Participate in the continuous improvement of data engineering practices, staying up-to-date with industry trends and best practices
- Explore and implement new technologies, tools, and frameworks that enhance the data engineering and processing capabilities of the team
- Hands-on experience with Power BI demonstrating how data architecture leads to efficient reporting and analytical tools