Data Engineer Job Description Template
Our company is looking for a Data Engineer to join our team.
Responsibilities:
- Participate in design discussions to improve our existing frameworks;
- Gather requirements, assess gaps and build roadmaps and architectures to help the analytics driven organization achieve its goals;
- May begin to develop sphere of influence with other teams;
- Handle multiple projects and meet deadlines;
- Research and evaluate new methods and tools to improve data gathering processes;
- Create and maintain data pipelines;
- Create and maintain ETL processes to be used by reporting;
- Recommend ways to improve data reliability, efficiency and quality;
- Collaborate with ML, data scientists, and Legal to design and implement compliant, secure, and robust feature stores;
- Work with new data models that provide intuitive analytics;
- Health: Medical, dental and vision;
- Prior experience with HR data is a plus;
- Transforming existing ETL logic into Hadoop Platform;
- Analyze and track forecast accuracy to target areas for improvement;
- Building end-to-end data integration and data warehousing solutions for analytics teams.
Requirements:
- Bachelor’s Degree in Computer Science, Computer Engineering or a closely related field;
- Ability to work in a team environment that promotes collaboration;
- Munging poorly formatted or unstructured data;
- 2+ years of experience implementing scalable data architectures;
- Excellent communication and collaboration skills;
- Strong skills Python programming language, extensive knowledge in Python libraries/frameworks to create pipelines to cleanse and manipulate data;
- Experience in building machine learning models;
- Fluent in Python and experience containerizing their code for deployment;
- Understanding the importance of picking the right data store for the job. (columnar, logging, OLAP, OLTP etc.,);
- 3+ years of experience with SQL and relational databases;
- You know how to work with high volume heterogeneous data, preferably with distributed systems such as Hadoop;
- Experience operating a workflow manager such as Airflow;
- Knowledge of Machine Learning concepts, applications, and libraries, particularly recommender systems, NLP, classification and clustering techniques;
- Solid analytical skills and demonstrated problem-solving ability;
- Experience with Agile implementation methodologies.