Data Engineer transforming data into easily analyzable formats at Sprout Solutions. Designing systems and frameworks to support data science initiatives in the HR tech space.
Responsibilities
Transforming data into a format that can be easily analyzed
Designing and developing Sprout’s data system
Processing and extracting data features
Deploying the data science team’s machine learning models
Supporting software engineers, architects and data scientists on data initiatives
Ensuring optimal data delivery architecture is consistent throughout ongoing projects
Building, optimizing and maintaining conceptual, logical and physical database models
Developing database solutions to store and retrieve information
Assembling datasets that meet functional/non-functional business requirements
Building the infrastructure for optimal ETL from a wide variety of data sources
Monitoring data integrity and adopting appropriate tools
Improving system performance
Optimizing or re-designing data architecture to support Sprout’s next generation of products and data initiatives
Designing, developing, testing and deploying web service APIs
Working with Data Scientists to identify future needs and requirements
Deploying models and algorithms developed by the Data Science team
Requirements
Extensive knowledge on databases (SQL and/or NoSQL) and data engineering best practices
Expertise in SQL and other programming languages(e.g. Python, Java, Scala, shell scripting etc.)
Experience with data modeling (data warehouse, data lake) and designing data storage schemes
Familiarity with data engineering and ETL software tools, hadoop, spark, talend, SSAS, etc. is also helpful
Experience building and optimizing data pipelines, architecture and datasets
Experience in software development
Experience with Azure
A successful history of manipulating, processing and extracting value from large disconnected datasets
Familiarity with data visualization tools (e.g. PowerBI)
Familiarity with agile development as a project management methodology is a plus
Strong problem-solving and analytical skills
Must be self-motivated and comfortable supporting the data needs of multiple teams, systems and products
A good team player and willingness to learn
Strong innate desire and proven track record of continuous self-improvement (in learning, job expansion, extracurricular activities, etc.)
Data Engineer managing payment processing and data accuracy while collaborating with financial teams. Building and optimizing data pipelines for transactional data in a hybrid work environment.
Data Engineer building analytical tools for Dry Bulk market data operations at Kpler. Join a team of over 700 experts transforming data into actionable strategies.
Data Engineer developing tools for maintaining data integrity in cargo tracking at Kpler. Collaborating with analysts and engineers to enhance data quality management.
Lead Azure Data Engineer designing and optimizing data ecosystems on Microsoft Cloud. Responsible for building scalable data platforms and pipelines for analytics and reporting.
Data Engineer providing support for IBM DataStage ETL jobs at Callibrity. Collaborating with stakeholders and working to modernize technology solutions in a hybrid work environment.
Cloud Data Engineer implementing tailored solutions for Volkswagen Group data processing. Building ETL/ELT pipelines while collaborating with technical experts.
Data Engineer responsible for building scalable data infrastructure that supports data - driven decisions. Collaborating with team to maintain systems and unlock data value for organizations.
Data Engineer designing and optimizing data pipelines using Databricks and Google Cloud Platform. Collaborating with analysts and scientists to deliver high - quality data products.