Senior Data Engineer / Architect

Enable Data Incorporated

8 years

4 - 8 Lacs

hyderābād

Posted:2 weeks ago| Platform: GlassDoor logo

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Skills Required

data azure databricks kafka architecture pyspark python sql spark design apache processing integration integrity security storage analytics tuning engineering software etl pipeline coding

Work Mode

Remote

Job Type

Part Time

Job Description

Experience Required: 8+Years
Mode of work: Remote
Skills Required: Azure DataBricks, Eventhub, Kafka, Architecture,Azure Data Factory, Pyspark, Python, SQL, Spark
Notice Period : Immediate Joiners/ Permanent/Contract role (Can join within September 15th 2025)

Design, develop, and maintain scalable and robust data solutions in the cloud using Apache Spark and Databricks.
Gather and analyse data requirements from business stakeholders and identify opportunities for data-driven insights.
Build and optimize data pipelines for data ingestion, processing, and integration using Spark and Databricks.
Ensure data quality, integrity, and security throughout all stages of the data lifecycle.
Collaborate with cross-functional teams to design and implement data models, schemas, and storage solutions.
Optimize data processing and analytics performance by tuning Spark jobs and leveraging Databricks features.
Provide technical guidance and expertise to junior data engineers and developers.
Stay up to date with emerging trends and technologies in cloud computing, big data, and data engineering.
Contribute to the continuous improvement of data engineering processes, tools, and best practices.

Requirements:

Bachelor’s or master’s degree in computer science, engineering, or a related field.
10+ years of experience as a Data Engineer, Software Engineer, or similar role, with a focus on building cloud-based data solutions.
Strong knowledge and experience with Azure cloud platform, Databricks,EventHub,Architecture,Spark,Kafka, ETL Pipeline,Python/Pyspark, SQL EventHub, Copilot Studio..
Strong experience with cloud platforms such as Azure .
Experience with big data systems, including Apache Spark / Kafka
Experience contributing to the architecture and design of large-scale distributed systems
Expertise in Databricks Lakehouse Platform, its architecture, and its capabilities.
Experience building production pipelines using Databricks and Azure services
Experience with multiple coding languages such as Python or SQL.

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