Data Engineer(Python, Databricks, SQL, AWS)

Summary

We are looking for a Data Engineer role. This role is strictly involved in the development of the product and does not involve access to Protected Health Information (PHI) & Personally Identifiable Information (PII) or any secured/confidential client data. The work is limited to application development & demo and does not include handling or processing of sensitive health information.

Your role in our mission

• Design, develop and deploy pipelines including ETL-processes using Apache Spark Framework.

• Monitor, manage, validate, and synthetic test data extraction, movement, transformation, loading, normalization, cleansing and updating processes in product development.

• Coordinates with the stakeholders to understand the needs and delivery with a focus on quality, reuse, consistency, and security.

• Collaborate with team-members on various models and schemas.

• Collaborate with team-members on documenting source-to-target mapping.

• Conceptualize and visualize frameworks

• Communicate effectively with various stakeholders.

What we're looking for

• Bachelor's degree in computer sciences or related field

• 3 years of relevant experience and equivalent education in ETL Processing/data architecture or equivalent.

• 3+ years of experience working with big data technologies on AWS/Azure/GCP

• 2+ years of experience in the Apache Spark/DataBricks framework (Python/Scala)

• Databricks and AWS developer/architect certifications a big plus

• Strong project planning and estimating skills related to area of expertise

• Strong communication skills

• Good leadership skills to guide and mentor the work of less experienced personnel

• Ability to be a high-impact player on multiple simultaneous engagements

• Ability to think strategically, balancing long and short-term priorities

What you should expect in this role

• Fast-paced, challenging and rewarding work environment.
• Work life balance.
• Remote working.
• Will required late evening work to overlap US work hours, whenever it is required.