Design, build, optimize, and maintain scalable data pipelines and analytical datasets supporting analytics, machine learning, and AI use cases.
Compensation
The anticipated compensation for this position is USD $123,650.00/Yr. - USD $203,150.00/Yr. depending on experience and qualifications.
Responsibilities
Design, build, optimize, and maintain scalable data pipelines and analytical datasets
Build reliable data ingestion, transformation, and feature pipelines across large-scale product telemetry, customer, behavioral, feedback, and operational datasets
Establish strong practices around data quality, observability, reliability, performance, and governance to ensure datasets are trusted and ready for analysis and modeling
Use Python, SQL, Spark, and modern cloud data technologies to process, transform, analyze, and derive insights from large-scale datasets
Analyze product telemetry, usage, behavioral, customer feedback, support, and operational datasets to identify trends, patterns, anomalies, friction points, and opportunities
Requirements
Bachelor's or higher degree in Data Science, Machine Learning, Statistics, Applied Mathematics, Computer Science, or a related discipline
We are seeking an experienced Senior Data Engineer (Microsoft Fabric) to join our Data & Analytics team and support a large-scale data modernisation programme. This strategic initiative focuses on migrating the organisation's analytics platform from Oracle to Microsoft Fabric.
Responsibilities
Design, develop, and deploy end-to-end data pipelines in Microsoft Fabric.
Leverage Change Data Capture (CDC) and Fabric Mirroring capabilities to enable real-time data replication and unified analytics.
Support the migration of semantic models and analytical workloads from Oracle to Microsoft Fabric.
Build, optimise, and maintain scalable data integration and transformation solutions using PySpark and SQL.
Develop and enhance metadata-driven ingestion and orchestration frameworks.
Requirements
Nice to have: Metadata-driven ingestion and orchestration frameworks
Lead design and architecture of scalable data platforms on GCP, manage and mentor a team of data engineers, and drive data pipeline development and modernization initiatives.
Locations (2)
Bangalore, Karnataka, India
Chennai, Tamil Nadu, India
Responsibilities
Lead the design and architecture of scalable, resilient, and high-performance data platforms on GCP
Define and implement data engineering best practices, including data modeling, pipeline orchestration, and data governance
Architect solutions using Big Data technologies such as Apache Spark, Hadoop ecosystem, and distributed systems
Drive end-to-end data pipeline development using Scala, Spark, and modern ETL/ELT frameworks
Lead development of batch and real-time data processing pipelines leveraging GCP services
Implement the design and architecture of scalable, resilient, and high-performance data platforms on Google Cloud (GCP) and drive end-to-end data pipeline development.
Locations (2)
Bangalore, Karnataka, India
Chennai, Tamil Nadu, India
Responsibilities
Implement the design and architecture of scalable, resilient, and high-performance data platforms on Google Cloud (GCP)
Implement data engineering best practices, including data modeling, pipeline orchestration, and data governance
Develop solutions using Big Data technologies such as Apache Spark, Hadoop ecosystem, and distributed systems
Drive end-to-end data pipeline development using Scala, Spark, and modern ETL/ELT frameworks
Lead development of batch and real-time data processing pipelines leveraging GCP services like BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage
Lead design, architecture, and delivery of scalable data platforms on Google Cloud, manage a team of data engineers, and drive data strategy and modernization initiatives.
Locations (2)
Bangalore, India
Chennai, Tamil Nadu, India
Responsibilities
Lead the design and architecture of scalable, resilient, and high-performance data platforms on GCP
Define and implement data engineering best practices, including data modeling, pipeline orchestration, and data governance
Architect solutions using Big Data technologies such as Apache Spark, Hadoop ecosystem, and distributed systems
Drive end-to-end data pipeline development using Scala, Spark, and modern ETL/ELT frameworks
Lead development of batch and real-time data processing pipelines leveraging GCP services
Design, develop, and optimize data pipelines using Snowflake and related technologies.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current range is $110,000 to $150,000.
Responsibilities
Design, develop, and optimize data pipelines using Snowflake capabilities.
Build and maintain ETL/ELT processes for data ingestion, transformation, and integration.
Support migrations from legacy systems to cloud-based platforms.
Develop and maintain database solutions using Microsoft SQL Server and SSIS.
Collaborate with business and technical teams to understand requirements and deliver data solutions.
Analytics Engineer II bridging business operations, data engineering, and business intelligence to develop trusted data products and AI-enabled analytical capabilities.
Responsibilities
Apply SQL and data transformation techniques to integrate, validate, and transform complex data
Design, build, maintain, and enhance curated datasets, semantic models, and reusable analytical products
Develop and maintain semantic layers, certified datasets, governed metrics, and business definitions
Prepare and optimize analytical data products and semantic models for AI-enabled and conversational analytics
Apply established standards for data quality, performance, and governance across analytical data products
Requirements
Bachelor's degree - BS in Computer Science, Information Systems, Data Analytics, Engineering, Statistics, Supply Chain, or a related field
Nice to have: Supply-chain or Manhattan-system experience
Nice to have: relevant training or certifications in SQL, analytics engineering, cloud data platforms, data governance, BI tooling, or AI-enabled analytics
Nice to have: familiarity with AI-enabled analytics, conversational analytics, predictive analytics
Lead data engineering initiatives within the GBO Advanced Capabilities Center of Excellence, designing, building, and maintaining enterprise-scale data pipelines and integration solutions.
Responsibilities
Build, maintain, and optimize data pipelines and workflows for reporting, analytics, and decision-support
Assist in connecting internal and external data sources and preparing curated datasets
Monitor data quality, troubleshoot issues, and ensure consistency and timeliness
Support post-implementation sustainment and continuous improvement of data-enabled capabilities
Collaborate with stakeholders to ensure data structures and engineering support for dashboards, models, and scenario analyses
Requirements
Bachelor’s degree in Data Engineering, Computer Science, Information Systems, Engineering, Analytics, or a related field
Master's degree in Data Engineering, Computer Science, Information Systems, Engineering, or a related technical discipline (preferred)
Nice to have: Master's degree (preferred)
Nice to have: Exposure to cloud technologies, data engineering frameworks, integration tools, and pipeline orchestration platforms
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Manager II, Data Engineering - Advanced Capabilities COEBristol Myers Squibb · Hyderabad, India