Lead Data Engineer

Job Description

Role Summary:

Baker Hughes has a new opportunity for Lead Data Engineer to join the team in Mumbai, India.

Essential Responsibilities:

• Work independently and contributes to the immediate team and to other teams across business.
• Work on enterprise-scale / complex project that require you to connect the business needs and domain with technical knowledge.
• Architect, design, optimize and implement data infrastructure and data engineering framework/solution. Collaborate with cross functional team of software developers & Data Scientist for its efficient integration with the application.
• Lead database technology evaluation options and propose best schema/design/optimizations for a database to meet the functional and non-functional requirements of the application.
• Implement processes and systems to monitor data quality, reliability and security
• Develop and maintain scalable data pipelines and builds out new API integrations
• Perform data analysis required to troubleshoot data related issues.
• Perform variety of in-depth data analysis, data modeling, and data design tasks on complicated datasets with potentially complex data integration scenarios.
• Create data infrastructure to support label collection, enable feature engineering, building training data, etc
• Develop backend services. Open to work on any language / script / technology as per the project need.
• Lead the team and provide technical coaching, reviews & guidance for building efficient data intensive solutions while being hands-on.
• Enable use of tools & frameworks for accelerated development.
• Implement and promote best practices for scalable and maintainable code.
• Expert in breaking down problems and estimate time for development tasks.
• Demonstrates the ability to make informed technology choices after due diligence and impact assessment.
• Understands whole product, its modules and the interrelationship between them while being an expert in the assigned component or module.
• Helps in designing interfaces and information exchange between modules. Serves as subject matter expert (SME) on one or more major modules.
• Possesses advanced domain knowledge and shows great customer focus.
• Demonstrates clarity of thinking to work through limited information and vague problem definitions

Qualifications/Requirements:

• Bachelors Degree in Computer Science or STEM Majors (Science, Technology, Engineering and Math).
• 8+ years of hands-on experience in building data centric services, data warehouse and data engineering framework/Solutions.

Desired Characteristics:

• Proficiency in data engineering concepts & platforms (Spark, Kafka, DASK, Hadoop, etc).
• Proficiency in designing and building the data pipelines, data model, data storage & real-time/batch processing that is efficient for Analytics pipeline.
• Ability to design and develop data engineering solutions that are efficient for analytics & BI applications while working with the cross-functional team of Software Developers/Architects and Data Scientists.
• Ability to derive data requirements, translate raw data into analysis-ready datasets, etc by understanding and applying business and domain knowledge & the consuming application/system.
• Proficiency in SQL /NoSQL Databases, basic & advanced database concepts.
• Experience in dealing with high volume of data, timeseries data, variety of data, unstructured data, etc.
• Awareness of frameworks/applications like MLFlow, Apache Beam, Flowable.
• Experience with libraries like Numpy and Pandas.
• Awareness of basic concepts of Data Science like data preparation, feature engineering, EDA, etc that influences data engineering.
• Experience in data warehousing principles and processes.
• Proficient in at least one of the programming languages (Java, .Net, Node). Knowledge of python is desired but not must.
• Ability to learn new technologies and take on hands-on development work as per business priorities.
• Knowledge of running ETL pipeline on GPUs is desired but not must.
• Knowledge of AWS or Azure services, docker/Kubernetes is desired but not must.

Keyskills :
sqljavadata warehousinginformaticapythondata sciencedata qualitydata analysisdata modelingdue diligencecomputer sciencedata integrationdata engineeringdata preparationdevelopment workunstructured datacommercial modelsprogramming languages