Goodway Group - Global Data Engineer
Requirements
• 5+ years of professional experience in data engineering, software engineering, or related technical roles, including substantial hands-on experience with production data systems. • Strong proficiency in Python and SQL, including building and optimizing complex data pipelines and transformations. • Python and SQL • Hands-on experience with Snowflake, including data warehousing, data modeling, query optimization, and performance tuning. • Snowflake • Experience designing, building, and maintaining production ETL/ELT pipelines using Apache Airflow or comparable orchestration frameworks. • ETL/ELT pipelines using Apache Airflow • Practical experience with AWS services supporting cloud-based data infrastructure. • Demonstrated experience designing scalable data architectures, data models, and warehouse structures. • Understanding of dimensional modeling, relational databases, data schemas, and data transformation techniques. • Experience implementing automated testing, data validation, monitoring, and troubleshooting processes. • Ability to identify performance bottlenecks, optimize data processing, and make informed decisions around infrastructure efficiency and costs. • Experience independently owning technical solutions from design through production. • Strong problem-solving skills and the ability to communicate technical decisions clearly with engineering and business stakeholders. • Experience working collaboratively with distributed, cross-functional teams. • Experience working with advertising technology (AdTech), marketing technology (MarTech), digital media, or agency data environments. • advertising technology (AdTech), marketing technology (MarTech), digital media, or agency data environments • Experience with financial technology (FinTech) or other industries managing complex, high-volume datasets. • Familiarity with advertising and marketing data sources, including campaign performance, attribution, customer segmentation, and measurement. • Experience with data clean rooms, privacy-conscious data collaboration, or large-scale data-sharing environments. • Experience designing and maintaining data taxonomies, metadata frameworks, and data governance practices. • Familiarity with dbt, Spark, Databricks, or similar data transformation and processing tools. • dbt, Spark, Databricks, or similar data transformation and processing tools • Experience with Rust or an interest in working with additional programming languages. • Experience supporting machine learning, AI, or advanced analytics initiatives. • Familiarity with CI/CD practices, infrastructure as code, and cloud cost management. • Check us out at www.goodwaygroup.com to learn more! • If you identify as a female candidate, and feel you can do this role even if there are a few things perhaps you've not done, please apply anyway! Goodway Group is 70% Female! We realize that men tend to apply for jobs when they can meet around 60% of the requirements for the role, where women tend to only apply when they know they meet 100% of the requirements. • If you identify as a female candidate, and feel you can do this role even if there are a few things perhaps you've not done, please apply anyway! Goodway Group is 70% Female!
Responsibilities
• Own delivery of production-grade data systems. Design, build, and maintain resilient data pipelines and platforms that support analytics, machine learning, and business operations. Your work is reliable under scale and built with long-term maintainability in mind. • Own delivery of production-grade data systems. • Drive system design for data architecture. Own the design of data models, pipelines, and storage solutions for team-level systems. You create scalable, flexible foundations that reduce complexity and improve onboarding for others. • Drive system design for data architecture. • Ensure high standards for code quality and reliability. Write well-tested, maintainable code and enforce best practices across data workflows. You proactively prevent issues such as data quality failures, pipeline fragility, and technical debt. • Ensure high standards for code quality and reliability. • Translate business needs into technical solutions. Connect data engineering decisions to business outcomes. You understand how data is used across the organization and ensure systems support accurate, timely, and actionable insights. • Translate business needs into technical solutions. • Collaborate across engineering, product, and data teams. Work closely with stakeholders to define requirements, prioritize work, and deliver solutions that align with business goals. You actively participate in design discussions and influence implementation decisions. • Collaborate across engineering, product, and data teams. • Mentor and unblock other engineers. Support team growth through code reviews, documentation, and technical guidance. You help others improve their approach to data engineering and keep projects moving forward. • Mentor and unblock other engineers. • Identify and mitigate risks early. Anticipate edge cases, scalability challenges, and data integrity risks. You surface issues early and help the team make informed tradeoffs. • Identify and mitigate risks early • Improve systems, tools, and processes. Introduce improvements to pipelines, testing, observability, and deployment practices. Your contributions lead to faster delivery, fewer incidents, and stronger overall system performance. • Improve systems, tools, and processes.
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