Title: Azure Data Engineer with Synapse
About Birlasoft:
Birlasoft, a global leader at the forefront of Cloud, AI, and Digital technologies, seamlessly blends domain expertise with enterprise solutions. The company’s consultative and design-thinking approach empowers societies worldwide, enhancing the efficiency and productivity of businesses. As part of the multibillion-dollar diversified CKA Birla Group, Birlasoft with its 12,000+ professionals, is committed to continuing the Group’s 170-year heritage of building sustainable communities.
Job title: - Data Engineer
Location: Pune (Relocation is considered)
Shift Timings: 4:00 PM to 1:00 AM IST
Interview: 2 round ( F2F & Virtual)
Laptop: Provided
GAP – 3 Months Gap only considered
Notice period -Immediate to 30 days
L1 will be scheduled Face to Face at Pune Office only and
L2 will be scheduled virtual.
Budget - 2,600,000.00
1.Project Overview: Candidate will be working in Risk metrics team to analyze large pool of data belonging to Identity Access Management and drive analytics to reduce the risk exposure.
3.Experience Level: 6.5+ Years relevant experience is must.
Level 2 (3-7 Yrs): 2500 INR/Hourly
4.Qualifications: - Bachelor's/master’s degree in computer science, Engineering, or a related field
5.Must have skills:
- Minimum of 6 years of Data Engineering Experience
- - Minimum of 6 years of Data Engineering Experience
- Build and manage scalable data lake solutions using Azure Data Lake Storage Gen2, integrating with services like Data Factory, Databricks, and Synapse Analytics.
- Design and optimize data pipelines for efficient ingestion, transformation, and storage using SQL, Python, and modern file formats such as Parquet and Delta Lake.
- Develop and deploy ETL solutions on Azure
- Excellent oral and written communication skills
- Self-starter with analytical, organizational, and problem-solving skills
-Experience with data modelling, data warehousing, and dimensional modelling concept
-Familiarity with data governance, data security.
6.Tasks & responsibilities
- Collaborate with team members and stakeholders to understand data and metric requirements
- Pull data from a variety of sources into a central data platform
- Structure datasets and calculate metrics based on requirements
- Develop automated scripts to automate otherwise manual processes
- Communicate concerns and data findings as they arise to the appropriate team members or stakeholders
- Present data findings and solutions in a way that is easy for non-technical team members and stakeholders to understand