Flexible work model
Work from home, from the office, or in a hybrid format that supports focus and collaboration.
ABOUT THE ROLE
In this role, you will contribute to building and maintaining scalable data solutions for a leading managed WordPress hosting platform. You will work with modern cloud-based data technologies to develop reliable data pipelines, improve data quality, and support analytics initiatives that help drive business decisions. Working within a distributed engineering team, you will collaborate across functions to deliver high-quality, maintainable, and well-governed data assets.
RESPONSIBILITIES
- Develop and maintain data replication and data processing pipelines in cloud environments using Python, Go, or third-party integration tools
- Design and implement data models using DBT to support analytics and reporting needs
- Build and maintain automated testing solutions to ensure data quality and reliability
- Contribute to CI/CD processes and automation practices for data platform development
- Monitor, troubleshoot, and optimize data jobs and pipeline performance
- Create and maintain technical documentation, including data models, system architecture, and ERDs
- Collaborate with cross-functional teams to deliver scalable data warehousing and analytics solutions
- Participate in code reviews and contribute to engineering best practices and data quality standards
- Identify opportunities to improve processes, tooling, and overall Data & Analytics Engineering practices
REQUIREMENTS
- 5+ years of experience in Data Engineering
- Hands-on experience with cloud platforms, preferably GCP (AWS or Azure also considered)
- Strong proficiency in Python, Go, or another scripting language
- Experience with DBT and advanced SQL for data transformation and analytics workloads
- Strong SQL debugging and query performance optimization skills
- Experience with data warehouse technologies such as BigQuery, Snowflake, or Redshift
- Knowledge of data modeling, normalization, and analytics data structures
- Experience with testing, automation, and CI/CD practices in data engineering environments
- Proficiency with Git and collaborative development workflows
- Experience working in Agile and distributed team environments
- Ability to translate business requirements into scalable data models and solutions
- Upper-intermediate or higher level of English
- Familiarity with Spark, Databricks, or other Big Data technologies is a plus
SoftServe is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, age, sex, nationality, disability, sexual orientation, gender identity and expression, veteran status, and other protected characteristics under applicable law. Let’s put your talents and experience in motion with SoftServe.
Role Summary
Location
Bulgaria, Poland, Ukraine
Work type
Remote/Office
Direction
Engineering & Technology
Subdirection
Data & Analytics
Tech level
Senior
Apply Now
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About us
We are a digital engineering and technology consulting company where expertise grows alongside people. For more than 30 years, we have been elevating technology: helping organizations navigate complex business challenges by combining deep engineering knowledge with thoughtful, research-backed innovation. Our teams work across key areas: digital engineering, data and analytics, Сloud, and AI/ML. In each, we deliver practical, scalable solutions rooted in real business needs and measurable human impact.
You bring your perspective and ambition. We create an environment where your work meets clarity, confidence, and purpose.
We offer
Compensation & Benefits
Competitive, market-based pay, benchmarked by role and location — plus health coverage, paid time off, wellness support, and learning opportunities.
People-first Leadership
Approachable leaders who communicate openly, keep teams close to the strategy, and support long-term planning.
Advanced tech communities
Stay close to AI/ML, Cloud, Quantum Computing, IoT, and Robotics communities, with projects built on modern frameworks.