Build, orchestrate and optimize data pipelines to extract, transform, and load (ETL) data from various sources into the organizations data warehouse or data lake.
Integrate data from diverse sources such as databases, APIs, streaming platforms, and file systems into cohesive data pipelines.
Implement data integration solutions that support real-time, batch, and incremental data processing.
Implement data quality checks and validation processes to ensure the accuracy, completeness, and consistency of data.
Develop and maintain high-performance data pipelines that seamlessly integrate data from various sources into data warehouses, data lakes, and other storage solutions.
Develop monitoring and alerting mechanisms to identify and address data quality issues proactively.
Optimize ETL (Extract, Transform, Load) processes for efficiency, reliability, and data quality.
Implement and manage data storage solutions, including relational databases, NoSQL databases, and distributed file systems.
Manage the infrastructure and resources required to support data engineering workflows, including compute clusters, storage systems, and data processing frameworks.
Implement security controls and data governance measures for an application to protect sensitive data and ensure compliance with regulatory requirements such as GDPR, CCPA, HIPAA, and PCI-DSS. Implement encryption, access controls, and auditing mechanisms to safeguard data privacy and integrity.
Write production-ready, testable code that adheres to engineering best practices and accounts for edge cases and error handling.
Develop comprehensive unit tests and integration tests to validate data pipeline functionality and data integrity.
Stay up to date with the latest data engineering tools, technologies, and methodologies, and evaluate their applicability to the teams needs.
Collaborate with business analysts, and other stakeholders to understand data requirements and translate them into robust engineering solutions.
Work closely with other engineering teams to integrate data solutions seamlessly into the overall technology ecosystem.
Participate actively in agile ceremonies, communicate progress, and manage dependencies effectively.
requirements-expected :
A relevant Bachelors or higher-education degree in Computer Science, Data Science, or related fields.
1-3 years of experience in a data engineering related role, with a focus on building scalable, reliable, and high-performance data systems.
Proficiency in programming languages such as Python, Java, or Scala.
Extensive experience with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud-based data platforms (e.g., AWS, Azure).
Expertise in data integration and ETL tools (e.g., Talend, Informatica, Apache NiFi).
Strong understanding of data warehousing, and data lake concepts and best practices.
Familiarity with CI/CD pipelines and application monitoring practices.
Certifications in data engineering (e.g., Azure Data Engineer, AWS Certified Data Engineer) are a plus.
Proven track record of designing and implementing data pipelines, data storage solutions, and data processing workflows.
Hands-on experience with distributed computing frameworks and cloud-based data services.
Demonstrated ability to collaborate with cross-functional teams and communicate technical solutions effectively.
Strong communications skills.
offered :
Perks & Benefits:
ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth and professional development. Our robust skills development programs, multiple career progression options and internal mobility paths and collaborative culture empowers you to thrive as an individual and global team member.
We are committed to giving our employees a flexible and connected way of working. All employees are expected to work from the office at least once per week. For those based outside of Warsaw, attendance will be required on specific days or for team events, which are anticipated to take place approximately two days per month. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections.
Travel:
Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures.
