Senior Data Engineer

We're growing rapidly and are seeking Data Engineers at multiple levels of experience; from experienced to highly experienced professionals—to build the next generation of our Talent Cloud platform through scalable data pipelines, storage systems, and analytics infrastructure that power our data-driven decision-making and AI capabilities. You'll design, build, and optimize data infrastructure that supports analytics, business intelligence, and product development, working with software engineers, data scientists, and product experts and providing technical leadership on projects in a culture that values innovation, ownership, and continuous learning.

Responsibilities:

• Design, develop, and maintain scalable data pipelines to collect, process, and store data from multiple sources.
• Build and optimize data infrastructure to support analytics, reporting, and AI/ML workloads.
• Implement event sourcing and streaming architectures using platforms (e. g., Kafka, AWS Kinesis) for real-time data processing.
• Apply data governance, security principles, and compliance frameworks to ensure data quality and regulatory adherence.
• Collaborate with data scientists, software engineers, and product teams to deliver reliable data solutions.
• Troubleshoot and resolve data-related issues while maintaining data quality and integrity.
• Contribute to best practices, frameworks, and tools for data engineering excellence.
• Drive improvements in data engineering practices and data architecture.
• Mentor data engineers and provide technical leadership on projects.

Requirements:

• Bachelor's degree in computer science, engineering, data science, or a related field (or equivalent professional experience).
• 4+ years of experience building data pipelines and systems.
• Proficiency in Python; familiarity with Java.
• Strong SQL skills and experience with relational and non-relational databases (e. g., SQL Server, PostgreSQL, MySQL, MongoDB).
• Experience with cloud platforms (AWS preferred) and data storage services (e. g., S3, Redshift).
• Experience with streaming platforms (e. g., Kafka, AWS Kinesis) and event-driven architectures.
• Strong understanding of data modeling, warehousing, and schema design principles.
• Experience with data transformation tools (e. g., dbt), BI platforms (e. g., Looker), and API development for data consumption.
• Knowledge of version control (Git), CI/CD pipelines, and security principles for data systems (encryption, IAM, compliance frameworks).
• Experience with user behavior tracking platforms (e. g., Snowplow, Google Analytics) is a plus.
• Strong analytical and problem-solving skills with intellectual curiosity.
• Strong communication and collaboration skills across both technical and non-technical teams.
• Demonstrated experience in mentoring engineers, leading technical projects, or driving architectural decisions.

Skills

AWS, Java, Kafka, Kinesis, MongoDB, MySQL, PostgreSQL, Python, Redshift, SQL, SQL Server, dbt