Sr. Data Engineer

Balfour Beatty India; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Balfour Beatty India is seeking an experienced Senior Engineer to design, build, and maintain scalable data pipelines, models, and platforms to power Analytics, BI, and AI/ML initiatives across the organization.

You will work across AWS, MS Fabric, Snowflake, and Redshift, implementing data quality and governance, and collaborating with stakeholders to resolve data issues and improve reliability.

Qualifications

• 6+ years of experience in data engineering or analytics.
• Bachelor's degree in CS/Engineering/IT or equivalent.
• Experience in Agile/DevOps environments.

Responsibilities

• Design, develop, and maintain scalable data pipelines across multiple source systems.
• Implement data quality frameworks including validation and integrity checks.
• Build optimized data models (Star schema, Lakehouse) for reporting and analytics.
• Monitor data reliability, including pipeline performance and failure handling.
• Support deployment pipelines using CI/CD and DevOps practices.

Skills

Data warehousing

Cloud platforms

SQL & data modelling

ETL & data integration

CI/CD & DevOps

Big data tooling

Education

Degree in Computer Science/Engineering/IT

Tools

Snowflake

Redshift

GCP data services

Job description

Balfour Beatty is a leading international infrastructure group delivering complex projects worldwide. Our IT and Digital teams enable business transformation through innovative data platforms, advanced analytics, and enterprise solutions.

About the Role

We are seeking an experienced Senior Engineer to design, build, and maintain scalable data pipelines, models, and platforms. This role plays a critical part in delivering high-quality, reliable data to support Analytics, Business Intelligence (BI), and AI/ML initiatives across the organization.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines across multiple source systems (ERP, CRM, APIs, files, event streams)
• Perform data ingestion, integration, and transformation to create clean, structured, and usable datasets
• Implement and maintain data quality frameworks including validation, completeness, and integrity checks
• Build optimized data models (Star schema, Lakehouse architecture) for reporting and analytics use
• Monitor and ensure data reliability, including pipeline performance, alerting, and failure handling
• Collaborate with data stewards, business users, and functional teams to troubleshoot and resolve data issues
• Implement data security controls including role-based access, row/column-level security, and classification
• Optimize ETL processes and improve performance and cost efficiency for analytics and AI workloads
• Support deployment pipelines using CI/CD practices and DevOps tools
• Maintain documentation, including ERDs, technical designs, and pipeline architecture
• Continuously enhance platform capabilities across AWS and MS Fabric ecosystems

Technical Skills & Expertise

• Strong hands-on experience in data warehousing
• Experience working with cloud platforms: AWS, Azure / MS Fabric, or similar
• Proficiency in SQL and data modelling techniques (Dimensional modelling, Data Warehousing)
• Experience with structured, semi-structured, and unstructured data
• Knowledge of data integration, APIs, and distributed data systems
• Familiarity with CI/CD tools and DevOps practices
• Hands-on exposure to performance tuning and optimisation
• Experience with ETL Tools & Strong in SQL codes
• Knowledge of Snowflake, Redshift, GCP data services
• Understanding of data governance, compliance, and security practices
• Experience handling large, complex datasets
• Exposure to AI/ML data pipelines

Qualifications & Experience

• 6+ years of experience
• Degree in Computer Science / Engineering / IT or equivalent experience
• Experience working in Agile / DevOps environments

Behavioural Skills

• Strong problem-solving and analytical mindset
• Excellent communication skills with both technical and non-technical stakeholders
• Collaborative and team-oriented approach
• Ability to manage multiple priorities and deliver under pressure
• Detail-oriented with a focus on high-quality outcomes
• Proactive learning attitude and curiosity