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dataeconomy

Databricks Engineer

Hyderabad · Senior

Older listing - lower visibility likelyVerified listingPosted 47d ago

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Skills required

12 listed
CI/CDTerm Life InsuranceApache SparkMachine LearningAccess ControlsExecution TimeDatabricksExtract Transform Load (ETL)+4 more
CI/CDTerm Life InsuranceApache SparkMachine LearningAccess Controls

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Job description

Job Title: Databricks Engineer Experience Level: 5 - 10 years Location: Hyderabad / Pune Qualification: BTech/MTech/MCA Mode of Work: Hybrid We are seeking a skilled and motivated Databricks Engineer to design, develop, and optimize scalable data solutions on the Databricks platform. The ideal candidate will have strong expertise in Apache Spark, Databricks architecture, ETL development, and modern data lakehouse concepts. This role will be responsible for building robust data pipelines, implementing best practices in data engineering, and supporting analytics and machine learning workloads. Key Responsibilities: Design, develop, and maintain scalable data engineering solutions using Databricks and Apache Spark. Create and deploy custom ETL/ELT pipelines to ingest, transform, and process large volumes of structured and unstructured data. Configure, manage, and optimize Databricks clusters for performance, scalability, and cost efficiency. Implement and manage Lakehouse architectures using Databricks best practices. Develop and maintain data workflows utilizing Delta Lake and Delta Live Tables (DLT). Design and implement Medallion Architecture (Bronze, Silver, Gold layers) for reliable and scalable data processing. Configure and govern data assets using Unity Catalog, ensuring data security, access control, and compliance. Collaborate with data architects, analysts, and business stakeholders to translate business requirements into technical solutions. Monitor data pipelines and troubleshoot performance or data quality issues. Optimize Spark jobs and workflows to improve processing efficiency and reduce execution time. Follow DevOps and CI/CD best practices for deployment and release management. Requirements 5-10 years of experience in Data Engineering or Big Data technologies. Strong understanding of Databricks architecture and core platform capabilities. Hands-on experience in setting up and managing Databricks clusters. Strong expertise in Apache Spark (PySpark/Scala Spark). Experience developing and deploying custom ETL pipelines in Databricks. Experience implementing Medallion Architecture within Databricks. Hands-on experience with Delta Live Tables (DLT). Strong understanding and implementation experience with Unity Catalog. Experience working with Delta Lake and Lakehouse architecture principles. Knowledge of data modeling, data quality, and performance tuning techniques. Familiarity with version control tools such as Git. Benefits Comprehensive Medical Coverage: Health insurance of INR 5.0 Lakhs for you and your family (up to 6 members), ensuring complete peace of mind. Robust Protection Plans: Group Personal Accident Insurance and Group Term Life Insurance to safeguard you and your loved ones. Retirement Benefits: PF and Gratuity provided as per standard government regulations. Flexible Work Options: Enjoy hybrid work arrangements & flexible working hours Generous Leave Policy: 21 days of annual leave, in addition to 10 company-declared holidays. Employee Well-being Spaces: Access to a dedicated break-out area with round-the-clock refreshments for relaxation and rejuvenation.

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Applicants who checked fit first are 3.1× more likely to hear back

Your match scoreFree · sign in
86Overall
64Skills
97Experience

Your score for this role already exists

ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.

Always free · no credit card · 1 tap with Google

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Why people use ASAI

Someone shared one job with you. ASAI keeps finding the rest.

  • Scored, not searched. Every role ranked against your actual profile.

  • Alerts as often as hourly. Reach new roles while the pile is still small.

  • Skill gaps, spelled out. See exactly which requirements you don't meet yet.

  • Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

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