IN-Manager_Azure Data Engineer_Data and Analytics_Advisory_Mumbai

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 

Job Requirements: 

Education : 

Bachelor or higher degree in computer science, Engineering, Information Systems or other quantitative fields 

Experience : 

1) Years of experience: 6 to 9 years relevant experience 

2) Deep and hands-on experience building, productionizing, maintaining and documenting reliable and scalable data infrastructure and data products in complex environments 

3) Hands on experience with: 

a) Spark for data processing (batch and/or real-time) - must 

b) Configuring Delta Lake on Azure Databricks – good to have 

c) Languages: SQL, pyspark, python - must 

d) Cloud platforms: Azure  - must 

e) Azure Data Factory (must) , Azure Data Lake (must), Azure SQL DB (must), Synapse (must), SQL Pools (must), Databricks (good to have) 

f) Building data solutions in Azure incl. data distributions and partitions, scalability, cost-management, disaster recovery and high availability 

g) Azure Devops (or similar tools) for source control & building CI/CD pipelines – good to have 

4) Experience in implementing large-scale distributed systems 

5) Customer management and front-ending and ability to lead large organizations through influence 

Desirable Criteria : 

• Strong customer management- own the delivery for Data track with customer stakeholders 

• Continuous learning and improvement attitude 

Key Behaviors : 

• Empathetic: Cares about our people, our community and our planet 

• Curious: Seeks to explore and excel 

• Creative: Imagines the extraordinary 

• Inclusive: Brings out the best in each other 

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: 

5 to 10 years relevant experience 

Education qualification: 

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

• Expected Joining: 3 weeks