Data Engineer
At a glance
Mid-level Data Engineering role at Altera. Bengaluru · full-time.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and tune data pipelines with Databricks, Azure Data Factory and Microsoft Fabric
- Create ETL and ELT workflows using PySpark, SQL and orchestration frameworks
- Design lakehouse and warehouse solutions, including data models on Databricks or Microsoft Fabric
- Deploy and maintain production pipelines with CI/CD and infrastructure-as-code practices
- Track pipeline performance, reliability and data quality, and apply governance and security controls
What you bring
- You have four to eight years in data engineering and strong knowledge of cloud data platforms
- You can work proficiently with PySpark, Azure Data Factory, Databricks and SQL
- You hold a bachelor's or master's degree in computer science, information systems, engineering or a related area
- You understand lakehouse and warehouse design, data modeling, and Microsoft Fabric or a similar analytics platform
Who this fits
This Bengaluru-based role suits a mid-level data engineer who works across technical and business teams and collaborates with analysts and data scientists. The schedule is Shift 1 in India.
From the employer
Job Details:
Job Description:
We are looking for a highly skilled Senior Data Engineer to join our Data & Analytics team and help the design and development of modern data platforms. This role focuses on building scalable, high-performance data solutions using tools such as Databricks,Microsoft Fabric, Azure Data Factory and PySpark. The ideal candidate will be passionate about data warehousing, data engineering, data architecture, automation, and DevOps practices, and will work closely with Business analysts, engineering team, Data Scientists to enable robust, real-time, and secure data operations.
Expert in data engineering, ETL/ELT, and modern data platforms such as (Databricks,MS Fabric, Synapse etc.)
Design, build, and optimize scalable data pipelines using Databricks, Azure Data Factory, and Microsoft Fabric.
Develop ETL/ELT workflows using PySpark, SQL, and data orchestration frameworks.
Architect and implement data Lakehouse and data warehouse solutions on Databricks/Microsoft Fabric.
The role requires a strong understanding of Data Warehousing, Data Modeling, data engineering principles, cloud computing, and the Microsoft Fabric platform
Strong in SQL development, including writing complex queries and stored procedures
Collaborate with data scientists and analysts to ensure efficient data delivery and model readiness.
Leverage CI/CD practices and infrastructure-as-code (IaC) to deploy and maintain data pipelines in production.
Monitor and troubleshoot data pipelines, ensuring performance, reliability, and data quality.
Enforce data governance, security, and compliance best practices across platforms.
Qualifications:
Bachelor’s or master’s degree in computer science, Information Systems, Engineering, or a related field.
4-8 years of experience in data engineering with strong knowledge of cloud data platforms.
Proficiency in PySpark, Azure Data Factory, Databricks and SQL.
Experience working with Microsoft Fabric or similar unified analytics platforms.
Solid understanding of data lakehouse and data warehouse architectures.
Solid understanding of Data modeling concepts.
Experience with Delta Lake, Synapse Analytics, and other Azure analytics services.
Familiarity with CI/CD pipelines, version control (e.g., Git), and deployment automation tools (e.g., Azure DevOps, GitHub Actions).
Strong problem-solving skills and ability to work across technical and business teams.
Good to have power bi and semantic model development experience.