Staff Data Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

When you join us at Thermo Fisher Scientific, you’ll be part of a smart, driven team that shares a passion for data exploration and discovery. With revenues of more than $40 billion and the largest investment in R&D in the industry. Our Mission is to enable our customers to make the world healthier, cleaner, and safer. Whether our customers are accelerating life sciences research, solving complex analytical challenges, improving patient diagnostics and therapies, or increasing productivity in their laboratories, we are here to support them. We give our people the resources and opportunities to make significant contributions to the world.

Location/Division Specific Information

• MLOpsTeam is part of R&D AI Engineering. Team is responsible for establishing MLOps standards, providing infrastructure and development of MLOps Framework for R&D teams of Thermo Fisher Scientific.

How will you make an impact?

Enabling our R&D teams at scaled, Staff Data Engineer will join our R&D AI Engineering team and will be responsible for working with data engineers and ML team to develop data management, data pipeline and data catalogues and responsible for providing complete data ops solutions. Staff Data Engineer must be able to collaboratively work in an Agile team to design, develop and maintain datalakes on Cloud-native technology stack. This position offers an exciting opportunity to work on processes that interface with multiple internal teams. The candidate will help contribute and propose a scalable design for development projects, pilots, and advanced best practices.

What will you do?

• You're a hands-on software architect who wants to make a difference! You work on complex problems that actively enhance our end users' experiences, drive growth in a dynamic company, and use analytics and dataops technologies.
• Deliver new solutions that solve business problems from idea through to development, deployment with monitoring of performance.
• Provide support and develop data pipelines for projects including data ingestion, data transformation, data analysis, querying, coding, visualization, modeling, and deployment.
• Design vendor-neutral datalake, data pipelines, and datastores, work with AWS, Databricks and Snowflake for specific business use cases.
• Be involved with many aspects of technical development, architecture, and automation to recommend and deliver sound software solutions.
• Build systems that integrate into our AI engineering datalake and align with other corporate and R&D data lakes.

Education:

• Bachelor’s degree in computer science, computer engineering, information systems, or related field, graduate degree preferred with 8+ years of experience.

Experience:

• Experience on Python, Scala and Golang.
• Experience on data modeling.
• Experience on ETL/data engineering
• Experience of AWS with services such as S3, Athena,Step Function, Redshift, Glue, Step Functions, CloudFormation, Kinesis, Spectrum, and more.
• Experience on spark, Hadoop.
• Experience of airflow, jupyter notebooks, presto, kafka, minio, docker, Kubernetes.
• Strong experience in ETL processes and database automation.
• Experience using Agile software development methodologies.
• Experience in wide variety of data formats like Parquet, Avro and Protobuff.

Knowledge, Skills, Abilities:

• Strong knowledge on dealing with structured or unstructured datasets
• Effective in documenting artifacts and processes with the ability to explain them to others
• Ability to think critically, and solve problems that are in line with business objectives and strategic vision
• Excellent oral and written communication skills to present technical information to both business and technology teams with clarity and precision.