Senior Engineer – Big Data & Data Ops


Job Overview

Position DescriptionAs a Senior Engineer – Big Data & Data Ops, you will join a team of Data and Analytics engineers including Data Scientists, ML Engineers and platform engineers to drive Danaher’s transformative Digital initiatives in IoT, Data and Analytics (Machine Learning/AI) applications targeted at multiple industrial segments such as Life Sciences, Diagnostics, Industrial manufacturing and environmental sciences. You will bring a strong track record in design, implementation and management of large-scale data sets. You will work closely with our business stakeholders, Data SMEs, cloud infrastructure team and Data Scientists to ingest data, build data models and create data pipelines that will form the foundation for Data Scientists for advanced modeling or other business use case analysis. You will bring your proficiency in multiple SQL/NoSQL databases to build and manage large scale data systems. You will leverage open source technologies and cloud-based AWS/Azure tools to process massive amounts of data and make it available in an organized structure both for proof of concept and production systems.As a senior member of the Data Engineering team, you will be called upon to guide other team members in technology and processes. You should be enthusiastic about learning new technologies and be able to craft solutions using them to provide new functionality to add value to our businesses. You will have excellent written and verbal communication skills as you will work very closely with diverse teams. You will work with a globally distributed Agile team in a fast-paced environment.Responsibilities* Provide technical leadership on designing, implementing high-performance, scalable, modular and reusable data processing pipelines and frameworks for advanced data-driven solutions based on advanced-analytics.* Articulate strategy within teams, effectively communicate with cross-functional teams, articulate solutions and influence leadership.* Partner with architecture, datasec, data scientists, DevOps/ModelOps, and business leaders to establish a strong thought leadership and trust for delivering projects on time and with a high degree of quality.* As subject matter expert in all things data, define and implement solutions for ambiguous problems, promote best industry practices in pipeline monitoring, data validation, testing, etc.* Drive meetings and lead discussions. Prioritize projects across the team and allocate resources to meet business and team goals. Drive internal process and productivity improvements and automate manual processes (Data Ops)* Develop, deploy and support assembly of large, complex data sets with optimal data pipeline architectures using big data frameworks such as Apache Kafka, Spark, Airflow or equivalents. Launch new data ingestion, extraction, transformation and loading processes to build key data sets to empower exploratory analysis and advanced analytics.* Build visualizations to provide insights into the data & metrics using visualization tools such as Tableau/Power BI or AWS QuickSight.* Partner with Data Scientists and domain specific data experts and other stakeholders including Architects, Product Managers/owners to identify and support data processing needs including data ingestion, data preparation, data clean-up and data readiness for development and production needs.* Partner with internal platform teams (Data Platform, ML Platform) to drive technical innovation* Serve as technical expert and mentor for core technologies in AWS/Azure data stacks. Evaluate new data technologies to build a scalable data platform.* Share in code and design reviews with agile team* Work with geographically distributed teams while maintaining highest standards in collaboration and communication.Requirements* 10+ years of proven experience in working with large scale data related stacks, technologies and tools* 7+ years of experience in developing highly scalable, reliable, reusable and real-time data processing pipelines for variety of data sources and formats.* 7+ years hands-on experience of working in scalable and distributed data environments in AWS or Azure: Kafka, Kinesis, Hadoop/Cassandra, Redis, RedShift, Azure Blob, Event Hubs or BigQuery* 7+ years of experience in database schema design and SQL* 5+ years of experience in building reusable data pipelines based on open source technologies such as Apache Spark/Airflow with Java/Scala; Must have experience in writing elegant, maintainable and testable code.* 5+ years of demonstrated experience in Python for data processing tasks* 5+ years of experience with a variety of data stores such as MongoDB, Cassandra, HBase, MySQL/Postgres* 3+ years of experience in creating reports and dashboards in Tableau/PowerBI or similar frameworks.* Ability to lead, define and set standards for Data Engineering, tooling & standards to improve the overall productivity and quality of Data Engineering team* Strong familiarity and knowledge of industry best practices and processes in Data quality and Data security (DataOps)* Ability to work with structured, semi-structured and unstructured datasets uncovering information and identifying complex links across different data sets* Demonstrated experience in designing and developing reusable code frameworks, libraries, and components.* Familiarity with various tools such as Kubernetes, Docker and a keen mindset for automation and familiarity with DevOps tools.* Must have experience in Agile development methods.* Must have knowledge of data management under privacy principles and applicable existing/emerging laws and regulations (ex: GDPR, CCPA etc)* Willingness to travel (<10%)

* Added advantage for familiarity in Machine Learning toolkits such as scikit-learn/TensorFlow or Pytorch.Danaher Corporation and all Danaher Companies are equal opportunity employers that evaluate qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity, or other characteristics protected by law. The “EEO is the Law” poster is available here.

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