What you will do: Lead a data engineering team. Collaborate with business stakeholders and technical teams to understand and analyze data requirements. Lead the design and implementation of data models and database structures that meet business needs. Profile, refactor, and tune performance in the database. Design and implement complex ETL processes to extract, transform, and load data from various source systems into the data warehouse. Ensure data integrity, consistency, and accuracy through robust data quality assurance measures. Review and support team members, providing guidance and mentorship.
Supervise and contribute to the data-driven strategy for the project, aligning it with business objectives. Required skills: 5+ years of hands-on experience in data engineering with Python and SQL. 3+ years of experience with AWS (Glue, S3, Athena, Lambda, DataZone)Strong experience with Airflow and SparkDrive the design and implementation of data warehouse and data lakes. Proficient in code versioning (git) and building CI/CD for data projects. Experience with requirement gathering and documentation. Will be a plus: Experience with NoSQL. What it’s like to work at Intellias: At Intellias, where technology takes center stage, people always come before processes.
By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual.
Join Intellias for a career where your perspectives and contributions are vital to our shared success.
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