Data Engineer designing and optimizing data pipelines using Databricks and Google Cloud Platform. Collaborating with analysts and scientists to deliver high - quality data products.
About the role
- Data Engineer responsible for designing and maintaining data pipelines at Pipedrive. Collaborating across teams to optimize data processing and insights for business operations.
Responsibilities
- Build and maintain data integrations and pipelines (ETL/ELT, APIs, webhooks, event streams, etc.).
- Design and implement reusable analytical models (using dbt, PySpark, and other modern tools).
- Work with teams across the company to identify data opportunities to drive impact, understand their needs, and help them get the most out of our Data Platform.
- Monitor and improve production data solutions, resolving issues proactively and during on-call rotations.
- Contribute to frameworks that make data processing more efficient and speed up insights.
- Contribute to engineering best practices through code reviews, design discussions, and knowledge sharing.
Requirements
- 3+ years of engineering experience, ideally with Python.
- Proven experience building and maintaining production-grade data pipelines.
- Experience with distributed data systems (like Spark or Flink) and cloud platforms (ideally AWS).
- Strong SQL and data modelling skills.
- Hands-on experience with the modern data stack (dbt, orchestration tools, etc.) and awareness of industry trends.
- Experience in at least one business domain, such as Customer, Marketing, or Finance.
- A clear communicator who enjoys working with others in an agile setup.
- A degree in Computer Science, Math, Statistics, or equivalent practical experience.
Benefits
- People-first culture - Be part of a team that values authenticity, champions collaboration, and supports each other—no egos, just teamwork.
- Unlock potential – Push boundaries, take ownership, and experiment with the latest technologies as we enhance our AI First Vision.
- Your well-being matters. Enjoy flexible hours, wellness perks, and SWAG.
- Think performance-based bonuses, 28 paid leave days, well-being days, compassionate leave, and even pawternal leave—because we take care of ourselves and our people.
- Grow with us – Whether through mentorship, coaching, or internal mobility, we invest in helping you unlock your potential. Open, honest feedback and clear communication are at our core.
- Help 100,000+ small and medium-sized businesses grow and succeed while doing meaningful, customer-driven work
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Data Engineer responsible for building scalable data infrastructure that supports data - driven decisions. Collaborating with team to maintain systems and unlock data value for organizations.
Associate Data Engineer supporting privacy engineering controls and executing privacy impact assessments in a financial services company. Collaborating across business units to ensure alignment with privacy regulations.
Data Engineer at CVS Health optimizing data pipelines and analytical models. Driving data - driven decisions with healthcare data for improved business outcomes.
Senior Data Engineer at CVS Health developing robust data pipelines for healthcare data. Collaborating with teams to provide actionable insights and integrate them with consumer touchpoints.
Senior Data Engineer supporting AI - enabled financial compliance initiative with data pipelines and ingestion processes. Collaborating with diverse teams in a mission - critical regulated environment.
Data Architect leading the definition and construction of cloud data architecture for Kyndryl. Participating in significant technological modernization initiatives, focusing on Google Cloud Platform.
Senior Data Engineer driving data intelligence requirements and scalable data solutions for a global consulting firm. Collaborating across functions to enhance Microsoft architecture and analytics capabilities.
Experienced AI Engineer designing and building production - grade agentic AI systems using generative AI and large language models. Collaborating with data engineers, data scientists in a tech - driven company.
Intermediate Data Engineer designing and building data pipelines for travel industry data management. Collaborating across teams to ensure reliable data for analytics and reporting.