As a Data Engineer, you will be required to interpret business needs and select appropriate technologies and have experience in implementing data governance of shared and/or master sets of data. You will work with key business stakeholders, IT experts, and subject-matter experts to plan and deliver optimal data solutions. You will create, maintain, and optimize data pipelines as workloads move from development to production for specific use cases to ensure seamless data flow for the use case. You will perform technical and non-technical analyses on project issues and help to ensure technical implementations follow quality assurance metrics. You will analyze data and systems architecture, create designs, and implement information systems solutions.
- Identify, design and implement internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes.
- Develop and design data pipelines to support an end-to-end solution.
- Develop and maintain artifacts (e.g. schemas, data dictionaries, and transforms related to ETL processes).
- Integrate data pipelines with AWS cloud services to extract meaningful insights.
- Work with stakeholders to support their data infrastructure needs and assist with data-related technical issues.
- Design and develop robust and functional dataflows to support raw data and expected data.
- Provide Tier 3 technical support for deployed applications and dataflows.
- Define and communicate a clear product vision for our client's software products, aligning with user needs and business objectives.
- Create and manage product roadmaps that reflect both innovation and growth strategies.
- Partner with a government product owner and a product team of 7-8 FTEs.
- Collaborate with the rest of data engineering team to design and launch new features.
- Coordinate and document dataflows, capabilities, etc.?
- Occasionally (as needed) support to off-hours deployment such as evening or weekends.?
Requirements
- Bachelor's degree or equivalent practical experience.
- Expertise in distributed computing frameworks to handle large-scale data processing.
- Familiarity working with Amazon Web Managed Services (AWS) or any other cloud environments.
- Working experience with datastores like PostgreSQL, S3, Redshift, MongoDB/DynamoDB, Redis, Elasticsearch/OpenSearch and SQL.
- Proficient utilizing Python with key libraries like pandas and PySark, NiFi, Airflow, AWS Lambda or similar technologies.
- Working knowledge with software platforms and services, such as, Docker, Kubernetes, JMS/SQS, SNS and Kafka.
- Familiar with Linux/Unix server environments.
- Experience with Agile development methodology.
- Publishing and/or presenting design reports.
- Coordinating with other team members to reach project milestones and deadlines.
- Working knowledge with Collaboration tools, such as, Jira and Confluence.
