Data Engineer
Data Engineer
Posted on :
15-03-2025
Employer Active
1 Vacancy
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Job Description
The Data Engineer will be responsible for designing building and optimizing scalable data pipelines and cloud based infrastructure under the guidance of the Lead Data Platform Engineer. This role involves working with Databricks SAP Data Sphere and AWS to enable seamless data ingestion transformation and integration across cloud environments to support enterprisewide analytics and datadriven decisionmaking as well as scalable efficient and secure data architecture. The Data Engineer will collaborate with crossfunctional teams to support analytics reporting and datadriven decisionmaking while ensuring performance security and data governance best practices.
Key Responsibilities:
- Design develop and maintain ETL/ELT pipelines for batch and streaming data processing.
- Implement data transformations cleansing and enrichment using Databricks (Spark PySpark SQL Delta
- Automate pipeline deployment and orchestration.
- Ensure data quality validation and consistency by implementing robust monitoring frameworks.
- Develop and maintain data lakehouse solutions on AWS.
- Optimize Databricks workflows job clusters and costefficiency strategies.
- Implement data governance lineage tracking and access controls using Databricks Unity Catalog.
- Build realtime and batch data integrations between SAP Data Sphere and cloudbased platforms.
- Develop logical and physical data models within SAP Data Sphere ensuring scalability and efficiency. Enable crosssystem data harmonization and replication between SAP and nonSAP environments.
- Monitor data pipeline performance identify bottlenecks and optimize query .
- Implement logging alerting and monitoring.
- Work with the Lead Data Platform Engineer to drive continuous improvements in scalability observability and security.
- Work closely with Architects Data Analysts and BI teams to support analytical solutions.
- Follow best practices in DevOps CI/CD and infrastructureascode (Terraform).
- Actively learn and apply the latest cloud data engineering and SAP Data Sphere advancements.
Data Pipeline Development & Optimization:
Lake MLflow) and SAP Data Sphere (Data Builder Business Builder).
Cloud Data Platform Implementation & Maintenance:
SAP Data Sphere & Data Integration:
Performance Monitoring & Troubleshooting:
Collaboration & Continuous Learning:
Key Requirements:
- 3 years of experience in data engineering cloud platforms and distributed systems.
- Proficiency in SQL Python and Spark.
- Experience with Databricks (Delta Lake Spark MLflow) and AWS data services.
- Experience with SAP Data Sphere SAP data modeling and integration frameworks (OData API management) will be a plus.
- Familiarity with data pipeline orchestration tools.
- Experience with DevOps & CI/CD pipelines (Terraform GitHub Actions Jenkins).
- Strong problemsolving skills and a passion for scalable and efficient data processing.
We offer:
- A dynamic team working within a zerobullshit culture;
- Working in a comfortable office at UNIT.City (Kyiv). The office is safe as it has a shelter;
- Reimbursement for external training for professional development;
- Ajaxs security system kit to use;
- Official employment with Diia City ;
- Medical Insurance;
- Flexible work schedule.
The Data Engineer plays a vital role in building and maintaining scalable efficient and secure data pipelines ensuring seamless SAP and cloud data integration. This role directly supports the Lead Data Platform Engineer in driving enterprisewide analytics AI/ML innovation and datadriven decisionmaking.
Employment Type
Full-Time
Key Skills
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