Data Engineer

GRIN is seeking a highly motivated, self-driven, and detail-oriented Data Engineer to design, develop and build highly scalable data systems. As a Data Engineer, you will have a high impact in defining data warehouse architecture, the underlying infrastructure, operational workflow, and building data pipelines for both data acquisition & data integration. You should have a demonstrated ability to work horizontally and vertically within our organization while maintaining approachability and humility with your fellow GRINners

You will focus on data quality, reliability, observability, performance, and security. This role requires a background in scaling data systems to keep up with a fast-growing product, working with a modern data stack, and implementing infrastructure and pipelines often from scratch.

We are a fast-paced, fun organization going through rapid growth, innovation, and solving technical challenges at an exponential scale. This is a rare opportunity to join a rapid growth company and experience career-changing impact at an ambitious tech company.

What You’ll Do:

• Collaborate with engineering and analytics teams to shape and drive the tactical and strategic development of data infrastructure, reporting, and analytical applications.
• Design, develop and own ETL pipelines, developing data infrastructure for scalable warehousing to power internal analytics for product and business teams to make data-informed decisions.
• Develop and maintain API integrations
• Create data tools and platforms to help streamline and automate workflows for the data  team and other teams across the organization
• Create data frameworks and processes to help with data quality, data integrity, data integration, & self-service.
• Continue to improve the performance and reliability of our data warehouse.
• Build robust scalable data processing and data integration pipelines using Python, Airflow, DBT, Kafka, Spark, REST API endpoints, and microservices to ingest data from a variety of external data sources to Google Big Query.

What You’ll Bring:

• 4+ years of experience as a Data Engineer in high data volume environments, preferably in the software, internet industry.
• Understanding in building pipelines to handle batch processing and streaming data at scale.
• Experience with data orchestration (Apache Airflow / Astronomer), IDEs (Dataform / DBT), transforming, developing data structures, metadata, dependency, and data workflows to support data analytics and data science
• Experience with data warehousing and ingestion, data modeling and transformation, code development, and data pipelining.
• Proficient in at least one distributed SQL framework (Hive, BigQuery, Spark, Snowflake, etc.).
• No-SQL, SQL: Strong database experience including ability to perform complex SQL queries.
• Python scripting language a must: expertise in gathering and cleaning data across multiple sources, creating API integrations, building ETL pipelines, and performing data aggregations.
• Demonstrated experience with web architecture, scaling, debugging code, performance analysis, and writing highly-optimized SQL and python scripts.
• Superior performance in prior roles with increasing levels of responsibility and independence; detail-oriented, demonstrated ability to handle multiple projects and solve complex problems.
• Fluency in project management – leading a project from inception and scoping to execution and postmortem. Flexible, adaptive, quick learner – works well in a collaborative, communicative environment.
• Excellent communication skills, both verbal and written; ability to condense complex information into simple language for the appropriate audience.
• Take initiative to drive projects forward, recommend and implement solutions
• Manage data projects from inception to completion negotiating requirements and deliverables with key stakeholders
• Excellent communication skills, both verbal and written; ability to condense complex information into simple language for the appropriate audience.