As a Big Data Engineer (Azure Databricks) at Nagarro, you'll be part of the Business Analytics & Insights (BAI) team, working on data solutions for various departments like Supply Chain, Finance, Operations, and more. Your responsibilities will include designing and implementing data pipelines using Azure Databricks, ensuring data quality and integrity, and working with event-based technologies for real-time data processing. You'll also be responsible for providing technical support, staying up-to-date with industry advancements, and recommending best practices for data lake solutions.
Proficiency in Data Modeling and Source System Analysis
Strong knowledge of PySpark and SQL
Experience with Azure Data Factory, Data Lake, SQL Data Warehouse (DW), and Azure SQL
Experience with Python for data engineering purposes
Ability to conduct data profiling, cataloging, and mapping
Good to have:
Familiarity with data visualization/exploration tools
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Company Description
👋🏼 We're Nagarro.
We are a digital product engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (18,500+ experts across 36 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in!
By this point in your career, it is not just about the tech you know or how well you can code. It is about what more you want to do with that knowledge. Can you help your teammates proceed in the right direction? Can you tackle the challenges our clients face while always looking to take our solutions one step further to succeed at an even higher level? Yes? You may be ready to join us.
Job Description
In this role, you will work with our Business Analytics & Insights (BAI) team, collaborating with cross-functional teams to deliver high-quality data solutions in areas such as Supply Chain, Finance, Operations, Customer Experience, HR, Risk Management, and Global IT.
Responsibilities:
Lead the technical planning for data migration, including data ingestion, transformation, storage, and access control within Azure Data Factory and Azure Data Lake.
Design and implement scalable, efficient data pipelines to ensure smooth data movement from multiple sources using Azure Databricks.
Develop reusable frameworks for the ingestion of large datasets.
Ensure data quality and integrity by implementing robust validation and cleansing mechanisms throughout the data pipeline.
Work with event-based/streaming technologies to ingest and process data in real-time.
Provide technical support to the team, resolving challenges during the migration and post-migration phases.
Stay current with the latest advancements in cloud computing, data engineering, and analytics technologies; recommend best practices and industry standards for data lake solutions.
Qualifications
4+ years of IT experience.
Minimum of 4 years working with Azure Databricks.
Proficiency in Data Modeling and Source System Analysis.
Strong knowledge of PySpark and SQL.
Experience with Azure components: Data Factory, Data Lake, SQL Data Warehouse (DW), and Azure SQL.
Experience with Python for data engineering purposes.
Ability to conduct data profiling, cataloging, and mapping for technical design and construction of data flows.
Familiarity with data visualization/exploration tools.
Additional Information
Technical leadership skills with the ability to guide and mentor teams.
Strong problem-solving capabilities, able to translate business requirements into data science solutions.
Excellent communication skills, with the ability to explain complex concepts to both technical and non-technical stakeholders.
Strong team player with excellent interpersonal and collaboration skills.
Ability to deliver high-quality results within specified timelines.