Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading technology company operates a large-scale data ecosystem that supports reporting, product analytics, marketing optimization, financial reporting, and other critical business functions. Its Data Engineering team develops database solutions, data pipelines, data structures, and data warehouse architectures that serve as the foundation for data-driven decision-making across the organization.
The organization is seeking a Senior Software Engineer, Data Engineering to help scale its data infrastructure, automation, and engineering tools to support growing business needs. The role requires a technically strong data engineering professional who can design high-performance data systems, improve data reliability, and collaborate effectively with both technical and non-technical stakeholders.
This is a hybrid position, and the successful candidate must be located near one of the organization’s engineering hubs in San Francisco, Sunnyvale, or Seattle.
About the Team
The Data Engineering team builds scalable database solutions for a wide range of use cases, including reporting, product analytics, marketing optimization, and financial reporting. Through the development of data pipelines, data structures, and data warehouse architectures, the team provides reliable and trustworthy data that supports critical business decisions.
Key Responsibilities
- Work with business partners and stakeholders to understand data requirements and translate them into technical solutions.
- Collaborate with engineering and product teams, as well as third-party partners, to collect and integrate required data.
- Design, develop, and implement large-scale, high-volume, and high-performance data models and pipelines for Data Lake and Data Warehouse environments.
- Develop and implement data quality checks and conduct quality assurance activities.
- Establish monitoring routines to improve data reliability and system performance.
- Improve the reliability, scalability, and efficiency of ETL processes.
- Manage a portfolio of data products that provide high-quality and trustworthy data.
- Support the onboarding and development of engineers joining the team.
- Contribute to the automation and continuous improvement of data infrastructure and engineering tools.
- Partner with cross-functional teams to ensure data solutions meet business and technical requirements.
Required Qualifications
- 5+ years of professional experience.
- 3+ years of experience in data engineering, business intelligence, or a similar role.
- Proficiency in programming languages such as Python or Java.
- 3+ years of experience with ETL orchestration and workflow management tools such as Airflow, Flink, Oozie, or Azkaban.
- Experience working with AWS and/or GCP.
- Strong expertise in database fundamentals, SQL, and distributed computing.
- 3+ years of experience working with distributed data ecosystems such as Spark, Hive, Druid, or Presto.
- Experience with streaming technologies such as Kafka or Flink.
- Experience working with Snowflake, Redshift, PostgreSQL, and/or other database management systems.
- Excellent communication skills with experience collaborating with technical and non-technical teams.
- Knowledge of reporting and business intelligence tools such as Tableau, Superset, or Looker.
- Ability to work effectively in a fast-paced environment.
- Self-starter with strong organizational and self-management skills.
- Ability to think strategically and analyze and interpret market and consumer information.
- Must be located near one of the designated engineering hubs: San Francisco, Sunnyvale, or Seattle.
Preferred Skills and Experience
- Strong understanding of large-scale data infrastructure and distributed systems.
- Experience designing high-volume and high-performance data pipelines.
- Experience improving ETL reliability, scalability, and monitoring.
- Ability to manage data products throughout their lifecycle.
- Strong analytical and problem-solving capabilities.
- Ability to collaborate effectively across engineering, product, business, and external partner teams.
- Experience mentoring or supporting other engineers.
Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals globally.
- No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
- No Client Relationship: This company is not a client of SpringCube unless stated.
- To Apply: Click the Apply button to be redirected to the hiring company’s application page for this job.
- No Liability: SpringCube is not liable for inaccuracies.
