TL;DR

Databricks Engineer (Data Engineering): Building and optimizing scalable data pipelines and managing the Human Capital Data Lake Databricks environment with an accent on secure data access and performance. Focus on administering clusters, implementing ABAC policies, and continuously optimizing data workflows.

Location: Hybrid in Gurugram, India

Company

%hirify_global% is a fast-growing digital innovation partner that transforms experiences and improves business outcomes for global brands.

What you will do

Administer and maintain Databricks workspaces, clusters, and configurations.
Design and implement reliable and performant data pipelines for new data sources.
Develop and enforce Attribute-Based Access Control (ABAC) policies for secure data access.
Write efficient PySpark code for data processing and automation tasks.
Collaborate with architecture and analytics teams to align data solutions with enterprise standards.
Continuously explore and implement innovative approaches to optimize data workflows and scalability.

Requirements

5 to 10 years of experience in Databricks and data engineering.
Proficiency in PySpark, SQL, Data Pipelines, Delta Lake, and Data Lake concepts.
Experience with Cloud Data Engineering platforms (Azure, AWS, GCP).
Ability to implement ABAC and Data Governance policies.
Skills in Cluster Management, ETL, ELT, Big Data, Spark, Data Transformation, and Data Orchestration.

Culture & Benefits

Award-winning culture fostering creativity and collaboration.
Opportunities for professional growth, mentoring, and continuous learning.
Competitive benefits supporting personal and family needs.
Engagement with world-class, Fortune 500 brands.
Flexible working options: work from home, office, or hybrid.
Corporate social responsibility programs.