Job Description

Analytical Wizards is part of the Definitive Healthcare family. We balance innovation with an open, friendly culture and the backing of a long-established parent company, known for its ethical reputation. We guide customers from what’s now to what’s next by unlocking the value of their data and applications to solve their challenges, achieving outcomes that benefit both business and society. Our people are our biggest asset, they drive our innovation advantage and we strive to offer a flexible and collaborative workplace where they can thrive. We offer industry-leading benefits packages to promote a creative and inclusive culture. If driving real change gives you a sense of pride and you are passionate about powering social good, we’d love to hear from you.

Job Description – Data Engineer

About the Role

We are looking for a candidate who is passionate about building scalable data pipelines, optimizing data workflows, and ensuring high data quality across systems. Candidates should demonstrate strong technical foundations, the ability to work independently, and a willingness to collaborate in a dynamic environment.

Core Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines to support business and analytical needs.
Work extensively with Databricks, Python, and PySpark to process large datasets.
Build and manage DAGs using Apache Airflow for workflow orchestration.
Collaborate with cross-functional teams to understand data requirements and translate them into efficient engineering solutions.
Develop and optimize complex SQL queries and participate in data modeling activities for relational and cloud data warehouses.
Work with Amazon S3 for data storage, ingestion, partitioning, and integration within broader data lake and pipeline ecosystems.
Ensure high standards of data quality, reliability, and performance across all data processes.
Contribute to documentation, best practices, and continuous improvement initiatives.

Core Technical Requirements

Python Programming
Strong experience writing clean, efficient Python code for data manipulation, automation, scripting, and ETL workflows.
Familiarity with widely used data libraries (e.g., pandas, numpy).
Databricks
Hands-on experience with Databricks for distributed data processing.
Proficiency in PySpark, Delta Lake, notebooks, and building scalable pipelines.
Orchestration Tools
Apache Airflow (Required): Ability to design, implement, and maintain complex DAGs for scheduling and orchestrating workflows.
Argo Workflows (Preferred): Experience with Kubernetes-native orchestration platforms is an added advantage.
SQL Skills
Advanced SQL expertise including writing complex queries, query optimization, and working with relational/cloud data warehouses.
Experience in data modeling and performance tuning.
Cloud Storage (Amazon S3)
Practical knowledge of S3 for ingestion, storage, data partitioning, access control, and integration as part of data lake architectures.