Senior Data Engineer
hatch I.T.
Get more replies from employers
Send a job-specific resume in minutes.
Job summary
Qualifications
- 5+ years of professional experience in data engineering or a related role.
- A strong foundation in Python including testing frameworks and ORMs.
- Experience building resilient pipelines using frameworks such as Dagster or Apache Airflow.
Responsibilities
- Design and implement robust, cloud-based data storage solutions.
- Develop, deploy, and maintain resilient ETL/ELT pipelines for data flow.
- Drive data governance and best practices for maintaining data health.
Skills
Education
Tools
Job description
hatch I.T. is partnering with Via to find a Senior Data Engineer. See details below:
An impressive mission requires an equally impressive Senior Data Engineer.
As a Senior Data Engineer at VIA, you will play a pivotal role in the growth of their solutions.
You will build the foundation that empowers their customers to harness AI for human‑centric, data‑driven decision‑making. You will work cross‑functionally with a high‑performing team of data professionals, developers, DevOps, and Client Delivery specialists who are already pushing the boundaries of what’s possible with AI.
Individuals who excel in this role are motivated by solving complex data accessibility challenges, holding a high bar for data quality and availability, and improving performance.
At VIA, their mission is to make communities cleaner, safer, and more equitable. VIA believes that by working across organizational boundaries, they can achieve greater collective good than they can individually. VIA overcomes digital barriers to collective action by providing the world’s most secure and simple data and identity protection solutions.
VIA is trusted by the U.S. Department of Defense and Fortune 100 companies around the globe to solve their toughest data and identity protection challenges. Using their Web3, quantum‑resistant, passwordless technologies (19 issued patents), VIA protects data against theft, manipulation, and misuse.
- Design and implement robust, cloud‑based data storage solutions, optimizing schemas for multi‑tenant environments while ensuring data accessibility and security and a high standard of trust and transparency
- Develop, deploy, and maintain resilient ETL/ELT pipelines for both real‑time streaming and batch processing, ensuring seamless data flow from raw ingestion to production‑ready applications
- Build and manage data access layers, including REST APIs and streaming services, to empower downstream users
- Drive data governance and best practices: Contribute across teams to recommend tools, processes, and best practices for maintaining data health, integrity, and security
- Support AI operations (MLOps) by managing versioning, containerization, and deployment of AI models
- Build monitoring and alerting systems to track data health and system performance, proactively identifying and remediating bottlenecks
- Bachelor’s degree or higher in Computer Science, Engineering, or Data Science
- 5+ years of professional experience in data engineering or a related role
- A strong foundation in Python (or equivalent), including testing frameworks (e.g., pytest) and ORMs (e.g., SQLAlchemy)
- You understand modularity and how to define clear scopes and responsibilities within a large codebase
- Proven experience architecting scalable relational and non‑relational (SQL/noSQL) schemas
- You manage the end‑to‑end database lifecycle, from initial design to production maintenance
- Expertise in maximizing system performance through advanced query tuning, strategic indexing, and execution plan analysis to eliminate technical bottlenecks
- Experience with one or more cloud‑based databases (e.g., AWS RDS, Azure Database)
- You are comfortable configuring compute resources, backups, and geolocation requirements
- Experience building resilient pipelines using frameworks such as Dagster or Apache Airflow
- You have a track record of maintaining data health for both real‑time streaming and batch processing
- A strong understanding of how data infrastructure integrates into the broader application architecture
- Experience with modern software development practices, including version control (Git), CI/CD pipelines, and a commitment to high‑quality, maintainable code
- Experience working with streaming data (e.g., Kafka) or running data models on the edge (e.g., Raspberry Pi, IoT devices)
- Familiarity with containerization and orchestration tools such as Docker and Kubernetes
- Experience architecting and consuming scalable RESTful APIs using standardized design principles and robust authentication protocols
- Familiarity with blockchain data indexing or privacy‑preserving data processing techniques
- Experience mentoring junior engineers or leading technical projects within a high‑performing team
- Self‑motivated and passionate about leaving everything they touch better than how they found it
- Firm believers that people should love what they do and are eager to build a culture that enables them to do their best work
- Creative problem solvers who respectfully challenge the status quo in the pursuit of excellence
- People who lead discussions with curiosity and value diverse perspectives
- Eager to explore new ideas, understand the power of feedback, and constantly seek opportunities to grow and develop their skills
- Strong team players who thrive in collaborative environments and celebrate the success of others
'/%3e%3cpath%20d='M101.744%2012.4726L102.894%2016.1947L99.0021%2013.2201L101.744%2012.4726ZM105.3%208.40937H100.488L99.0026%203.59473L97.5116%208.41047L92.7%208.40385L96.5965%2011.3834L95.1055%2016.1942L99.0021%2013.2196L101.408%2011.3834L105.3%208.40992V8.40937Z'%20fill='white'/%3e%3cdefs%3e%3clinearGradient%20id='paint0_linear_5593_1381'%20x1='90'%20y1='9.44471'%20x2='99'%20y2='9.44471'%20gradientUnits='userSpaceOnUse'%3e%3cstop%20stop-color='%2300AD70'/%3e%3cstop%20offset='0.998594'%20stop-color='%2300B67A'/%3e%3cstop%20offset='1'%20stop-color='%23DCDCE6'/%3e%3c/linearGradient%3e%3c/defs%3e%3c/svg%3e){kind=small}
