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June 7


From collecting and processing terabytes of data a day to improving and building new data assets, tools, and pipelines. Our ideal candidate thrives in a fast-paced consulting environment, relishes working with large transactional volumes and big data, enjoys the challenge of highly complex business problems and, above all else, is passionate about data and analytics. A successful candidate knows and loves working with technical tools, is comfortable accessing and working with data from multiple sources, and partners with the client to identify strategic opportunities and deliver results.

As a Senior Data Engineer at SFL Scientific, you will help enable organizations to collect, transform, and visualize data. You will design, build, maintain, and troubleshoot data processing systems with a particular emphasis on the security, reliability, fault-tolerance, scalability, fidelity, and efficiency of such systems. The Senior Data Engineer also analyzes data to gain insight into business outcomes, builds statistical models to support decision-making, and creates machine learning models to automate and simplify key business processes. You will be responsible for designing and implementing solutions using third-party technologies (e.g., different cloud providers) and SFL solutions.


Provide technical design leadership with the responsibility to ensure the efficient use of resources, the selection of appropriate technology, and use of appropriate design methodologies

Work closely with business/product stakeholders in understanding requirements and translating them to engineering requirements

Support and enhance data architecture, data instrumentation, define database schema, create ETL pipe­lining, generate reports/insights, a guide algorithm design

Define and evangelize data warehouse fundamentals and best practices

Work across the organization in optimizing data capture (parameters, metadata, etc.)

Work in DevOps to bring up new data systems and supporting existing data services

Evaluate SaaS solutions (BI, pipe­lining, etc.) and make build/buy recommendations

General Requirements:

Bachelor’s degree in Computer Science, Engineering, Math, Physics, or equivalent work experience

5+ years of software development experience

Proficient in SQL, NoSQL databases, and GNU Linux

Experience building secure, concurrent, distributed server applications

Experience in data science, analytics, or big data solutions [Hadoop, Spark, AWS, Python, etc.]

Experience with Scala, MongoDB, Cassandra, PostgreSQL, Docker, Kubernetes is required.

Ability to work collaboratively with a distributed team or remotely with clients

Other Skills/Experience:

Enable machine learning and data analysis

Model data and metadata to support dashboards, ad-hoc, and pre-built reporting

Adopt best practices in reporting and analysis: data integrity, analysis, validation, and documentation

Ability to engage clients and lead relevant data discussions

Preferred Qualifications:

AWS Certified DevOps Engineer; AWS Certified Solutions Architect; AWS Certified Big Data

Azure or Google Certified Professional Data Engineer

Master's or Ph.D degree

Please send cover letter, CV or resume to [email protected] or apply directly at https://sflscientific.com/careers/senior-data-engineer


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