Engineer I, Data Engineering

Understand and document scope and requirements through interactions with analysts and stakeholders. Design and develop scalable code based custom ETL pipelines using big data technologies on Cloud platform. Design and develop code to ingest data from a variety of data sources such as Relational databases, APIs and files. Develop Complex SQL transformations on Bigquery. Code and query Optimization. Follow and contribute to engineering best practices for source control using Github, release management, deployment etc. Provide production support, job scheduling/monitoring, ETL data quality, data quality reporting. Contribute to software development and business management by effectively solving business-related software problems through data modeling/analysis/prediction. Establish/support software and infrastructure that continuously grows to strategically analyze big data. Understand and implement software data analysis strategies that meet business strategy. Establish and operate software and infrastructure that can collect/analyze/predict big data (structured/unstructured). Design and operate software structure that can maintain data integrity. Proceed with software data model for business-related decision-making and evaluate data model’s consistency. Establish a software security system for data and protect from unauthorized users.

Bachelor’s degree in Computer Science, Applied Computer Science, Computer Applications, Computer Engineering, Information Technology, a related field, or a foreign equivalent plus 3 years post-baccalaureate experience in job offered or any engineering/IT related job titles.

Applicants must have 3 years of experience in the following: (1) statistical analysis and predictive modeling using Python; (2) ETL development using python and SQL; (3) GitHub, development IDEs including VS code.; (4) data manipulation using SQL; (5) design, execution, and measurement of A/B and multivariate tests; (6) GCP services including Bigquery, Kubernetes and Composer and Apache Airflow; (7) performing data analysis on data visualization dashboards Superset, Jupyterlab, Tableau or PowerBI; (8) software tools including Jira and Confluence; and (9) working in the big data domain including providing production support, job scheduling/monitoring, ETL data quality, and data quality reporting.

At Samsung, we believe that innovation and growth are driven by an inclusive culture and a diverse workforce. We aim to create a global team where everyone belongs and has equal opportunities, inspiring our talent to be their true selves. Together, we are building a better tomorrow for our customers, partners, and communities.