Senior Data Engineer

Velir is an established mid-sized agency with a top-tier portfolio of clients, ranging from the world’s largest non-profits to Fortune 500 brands. As of 2023, Velir acquired Brooklyn Data Company, a premier data and analytics consultancy focused on leadership, process improvement, implementation, and advanced analytics.

At Velir, we believe people are our greatest asset. Our culture is built on a foundation of trust, collaboration, and continued improvement. We strive for excellence in everything we do, embracing challenges as opportunities for growth. Our success is driven by a shared passion for making a positive impact on our customers, our communities and each other. We are a remote first company that offers competitive pay and excellent benefits.

Senior Data Engineers play a crucial role in helping our client organizations manage and leverage their data effectively. Their responsibilities include Data Architecture Design;
Data Warehousing;
Data Quality Assurance;
Scalability and Performance Optimization; and Data Security. As senior-level individual contributors, SDEs are also responsible for recommending and implementing data engineering tools and technologies that best suit the client’s needs. Because our clients are mostly US-based organizations, we look for the ability to communicate with professional proficiency in English, verbally and in writing.

• Data Engineering Leadership: Youare responsible for bridging technical gaps to lead and oversee various data engineering projects for our data solutions engagements. Youpossessadvanced data engineering knowledge and expertise, and your assignments, projects, and programs are of significant scope and/or complexity where effective decision-making requires navigating ambiguous or uncertain conditions.
• Cross-Team
  
  Collaboration:
  
  Youare responsible for contributing to alignment across the organization through influence and by translating context across different teams. You have a strong, foundational understanding of other Data Team functions, while also being able to translate these concepts for less technical colleagues.
• Project Enablement: Youare responsible for ensuring that large and/or more complex engineering projects are delivered in alignment with the appropriate business outcomes. As a senior+ member of the Data Engineering function, you serve as a mentor to data solutions team members, data engineering managers, and other data engineers, and may be embedded on a client team to unblock and upskill them.

• Programming languages (e.g. SQL, Python)
• Cloud-based data warehouses (e.g., Snowflake, Google Big Query)

• Data Movement. Optimizes data pipelines to achieve low latency, ensuringtimelyprocessing and delivery of data. Can design and implement real-time and /or micro-batch data processing solutions that handle high-volume data with low latency requirements.
• Data Warehousing. Acts as an internal resource for data warehousing, providing help with advanced techniques and strategies for novel scenarios.
• Programming. Has an authoritative or deep holistic understanding, deals with routine matters intuitively, able to go beyond existing interpretations, achieves excellence with ease.
• Technical Management: Is able to be a technical leader across a set of related team'sdomains, consistently pushing boundaries and exploring gaps in understanding.
• Data Infrastructure: You can design, build, andmaintainthe underlying data infrastructure for a complex, large-scale system that integrates with multiple disparate data sources.
• Data Modeling and Transformation: Comfortable with modeling and transforming extremely large and complex datasets in a performant and cost-efficient manner.
• MLOps: Understands and can execute the stepsrequiredto deploy a trained model into a production environment for offline or online scoring.

• Proven experience as a Data Engineer or related role, with a focus on designing and developing data pipelines.
• Strong programming skills in Python and SQL. Experience with Scala and Rust is a plus but not required.
• Deep knowledge of data warehousing and ETL/ELT processes.
• Intermediate / expertproficiencywith common data integration / orchestration platforms (e.g.,Fivetran, Azure Data Factory, Apache Airflow)
• Deep experience with at least one cloud data warehouse (Snowflake,Big Query, Databricks, or similar).
• Experience with streaming solutions such as Spark Streaming, Kafka, or Flink is desirable but…