Data Engineer Consultant II

Allstate India Private Limited; Bengaluru; On-site; INR 900,000 - 1,400,000; Full time

Job summary

Allstate India Private Limited in Bengaluru is seeking a Data Engineer to design, build, and operate scalable data pipelines that support analytics, reporting, and advanced use cases. You will focus on batch and streaming solutions using Apache Spark and cloud-native platforms, with Microsoft Fabric as a strong plus.

You will collaborate with analytics engineers, data scientists, product teams, and platform partners to deliver trusted, analytics-ready datasets while ensuring data quality,

Qualifications

• Strong experience as a Data Engineer building and operating production data pipelines.
• Hands-on experience with Apache Spark for large-scale data processing.
• Proficiency in Python, SQL, and data transformation best practices.
• Experience with cloud-based data platforms and storage (e.g., Data Lakes, Lakehouse architectures).
• Familiarity with Microsoft Fabric, One Lake, or similar analytics platforms (strong plus).
• Experience designing and optimizing data models for analytical workloads.
• Understanding of distributed data processing concepts, performance tuning, and fault tolerance.
• Experience with CI/CD, version control, and infrastructure-as-code concepts.

Responsibilities

• Design, build, and maintain scalable batch and streaming data pipelines using Apache Spark and cloud-native data technologies.
• Develop and optimize ETL/ELT workflows to ingest, transform, and curate data from diverse source systems into analytics-ready datasets.
• Implement data modeling and transformation logic to support reporting, dashboards, and downstream analytical and machine learning workloads.
• Build and manage data processing workloads within modern Lakehouse platforms, including Microsoft Fabric / One Lake (preferred).
• Ensure data quality, reliability, and consistency by implementing validation checks, monitoring, and reconciliation processes.
• Optimize Spark jobs for performance, cost efficiency, and scalability across large and complex datasets.
• Manage and evolve data schemas while handling schema drift and upstream source changes.
• Develop reusable frameworks, libraries, and standardized patterns to improve data engineering productivity and consistency.
• Implement CI/CD pipelines for data workloads to enable automated testing, deployment, and rollback.
• Monitor data pipelines and jobs, troubleshoot failures, and resolve performance or data quality issues.
• Partner with analytics engineers, BI developers, and data scientists to understand data requirements and deliver curated datasets.
• Collaborate with platform, security, and governance teams to ensure data security, compliance, and proper access controls.
• Contribute to Agile delivery processes, including sprint planning, design reviews, and continuous improvement initiatives.

Skills

Apache Spark

Python

SQL

Data Pipelines

Cloud Platforms

ETL/ELT

CI/CD

IaC

Data modeling

Data quality

Big data

Tools

Microsoft Fabric

One Lake

Job description

Job Summary

Allstate's Data Analytics Technology organization is seeking a Data Engineer to design, build, and operate scalable, reliable, and high performing data pipelines that support enterprise analytics, reporting, and advanced data use cases. In this role, you will focus on building robust batch and streaming data solutions using Apache Spark and modern cloud data platforms. Experience with Microsoft Fabric is a strong plus.

You will work closely with analytics engineers, data scientists, product teams, and platform partners to transform raw, complex data into trusted, analytics ready datasets. This role plays a critical part in enabling data driven decision making by ensuring data quality, performance, scalability, and operational excellence across the data platform.

Key Responsibilities

• Design, build, and maintain scalable batch and streaming data pipelines using Apache Spark and cloud-native data technologies.
• Develop and optimize ETL/ELT workflows to ingest, transform, and curate data from diverse source systems into analytics-ready datasets.
• Implement data modeling and transformation logic to support reporting, dashboards, and downstream analytical and machine learning workloads.
• Build and manage data processing workloads within modern Lakehouse platforms, including Microsoft Fabric / One Lake (preferred).
• Ensure data quality, reliability, and consistency by implementing validation checks, monitoring, and reconciliation processes.
• Optimize Spark jobs for performance, cost efficiency, and scalability across large and complex datasets.
• Manage and evolve data schemas while handling schema drift and upstream source changes.
• Develop reusable frameworks, libraries, and standardized patterns to improve data engineering productivity and consistency.
• Implement CI/CD pipelines for data workloads to enable automated testing, deployment, and rollback.
• Monitor data pipelines and jobs, troubleshoot failures, and resolve performance or data quality issues.
• Partner with analytics engineers, BI developers, and data scientists to understand data requirements and deliver curated datasets.
• Collaborate with platform, security, and governance teams to ensure data security, compliance, and proper access controls.
• Contribute to Agile delivery processes, including sprint planning, design reviews, and continuous improvement initiatives.

Required Qualifications

• Strong experience as a Data Engineer building and operating production data pipelines.
• Hands-on experience with Apache Spark for large-scale data processing.
• Proficiency in Python, SQL, and data transformation best practices.
• Experience with cloud-based data platforms and storage (e.g., Data Lakes, Lakehouse architectures).
• Familiarity with Microsoft Fabric, One Lake, or similar analytics platforms (strong plus).
• Experience designing and optimizing data models for analytical workloads.
• Understanding of distributed data processing concepts, performance tuning, and fault tolerance.
• Experience with CI/CD, version control, and infrastructure-as-code concepts.
• Strong problem‑solving skills and ability to troubleshoot complex data issues.
• Excellent communication skills and ability to collaborate across technical and non‑technical teams.
• 4+ years of experience in data engineering or equivalent role (preferred).

Preferred / Nice‑to‑Have Skills

• Experience with real‑time or event‑driven data processing.
• Familiarity with data governance, metadata management, and data quality frameworks.
• Exposure to orchestration tools and workflow management systems.
• Experience supporting analytical, reporting, or machine learning use cases.

Supervisory Responsibilities

This job does not have supervisory responsibilities.