Azure Data Engineer

Job Description & Summary:  

A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. 

Responsibilities: 

• Designs, implements and maintains reliable and scalable data infrastructure 

• Writes, deploys and maintains software to build, integrate, manage, maintain, and quality-assure data 

•Develops, and delivers large-scale data ingestion, data processing, and data transformation projects on the Azure cloud 

• Mentors and shares knowledge with the team to provide design reviews, discussions and prototypes 

• Works with customers to deploy, manage, and audit standard processes for cloud products 

• Adheres to and advocates for software & data engineering standard processes (e.g. Data Engineering pipelines, unit testing, monitoring, alerting, source control, code review & documentation) 

• Deploys secure and well-tested software that meets privacy and compliance requirements; develops, maintains and improves CI / CD pipeline 

• Service reliability and following site-reliability engineering standard processes: on-call rotations for services they maintain, responsible for defining and maintaining SLAs. Designs, builds, deploys and maintains infrastructure as code. Containerizes server deployments. 

• Part of a cross-disciplinary team working closely with other data engineers, Architects, software engineers, data scientists, data managers and business partners in a Scrum/Agile setup 

Mandatory skill sets: 

‘Must have’ knowledge, skills and experiences  

Synapse, ADF, spark, SQL, pyspark, spark-SQL, 

Preferred skill sets: 

‘Good to have’ knowledge, skills and experiences  

Cosmos DB, Data modeling, Databricks, PowerBI, experience of having built analytics solution with SAP as data source for ingestion pipelines. 

Depth: Candidate should have in-depth hands-on experience w.r.t end to end solution designing in Azure data lake, ADF pipeline development and debugging, various file formats, Synapse and Databricks with excellent coding skills in PySpark and SQL with logic building capabilities. He/she should have sound knowledge of optimizing workloads. 

Years of experience required: 

6 to 9 years relevant experience 

Education qualification: 

• BE, B.Tech, ME, M,Tech, MBA, MCA (60% above) 

• Expected Joining: 3 weeks