Work with stakeholders to understand data requirements and architect end-to-end ETL solutions.
Design and maintain data models, including schema design and optimization.
Develop and automate data pipelines to ensure quality, consistency, and efficiency.
Lead the architecture and delivery of key modules within data platforms.
Build and refine complex data models in Power BI, simplifying data structures with dimensions and hierarchies.
Write clean, scalable code using Python, Scala, and PySpark (must-have skills).
Test, deploy, and continuously optimize applications and systems.
Lead, mentor, and develop a high-performing data engineering team, fostering a culture of collaboration, innovation, and continuous improvement while ensuring alignment with business objectives.
Mentor team members and participate in engineering hackathons to drive innovation.
Requirements
7+ years of experience in Data Engineering, with at least 2 years in a leadership role.
Strong expertise in Python, PySpark, and SQL for data processing and transformation.
Hands-on experience with Azure cloud computing, including Azure Data Factory and Databricks.
Proficiency in Analytics/Visualization tools: Power BI, Looker, Tableau, IBM Cognos.
Strong understanding of data modeling, including dimensions and hierarchy structures.
Experience working with Agile methodologies and DevOps practices (GitLab, GitHub).
Excellent communication and problem-solving skills in cross-functional environments.
Ability to reduce added cost, complexity, and security risks with scalable analytics solutions.
Nice to have:
Experience working with NoSQL databases (Cosmos DB, MongoDB).
Familiarity with AutoCAD and building systems for advanced data visualization.
Knowledge of identity and security protocols, such as SAML, SCIM, and FedRAMP compliance.
Benefits
Health insurance fully paid–Spouse, children, and Parents
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