Design, develop, and deploy end-to-end data engineering solutions using Databricks, Apache Spark, PySpark, Python, and SQL.
Build scalable and efficient ETL / ELT pipelines for data ingestion, transformation, and integration from various sources.
Work with data warehousing solutions and ensure high-performance data processing and storage.
Engage directly with clients to gather requirements, propose solutions, and manage delivery expectations.
Collaborate with data scientists, analysts, and other engineers to support ML model deployment, MLOps, and advanced analytics use cases.
Implement data modeling, data architecture, and adhere to best practices in modern data platform design.
Utilize CI / CD tools such as GitHub, Azure DevOps, and Pipelines for version control, testing, and production deployment.
Manage technical project delivery, including scope, timelines, and technical documentation.
Troubleshoot performance issues and optimize distributed computing processes using Apache Spark.
Continuously learn and apply new features and tools to enhance existing solutions and architectures.
Required Skills & Experience :
4+ years of experience in data engineering, data platforms, and data analytics.
3+ years hands-on experience with Databricks, Apache Spark, PySpark, Python, and SQL.
Experience working in client-facing roles or consulting environments.
Strong understanding of data modeling, ETL processes, and cloud data architecture principles.
Working knowledge of at least two cloud platforms (AWS, Azure, GCP), with deep expertise in one.
Solid knowledge of Spark runtime internals and distributed computing.
Experience with CI / CD and deployment pipelines GitHub, Azure DevOps, etc.
Familiarity with MLOps concepts and production model support.
Preferred Qualifications :
Databricks Data Engineer Associate or Professional Certification (preferred or must be willing to obtain).
Experience with whiteboarding, architecture documentation, and delivering technical presentations.
Ability to manage technical conflict, communicate effectively, and handle multiple client engagements.
(ref : hirist.tech)
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Data Engineer • Hyderabad
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