data engineer

SoftServe is a digital engineering and technology consulting company that helps organizations navigate complex business challenges by combining deep engineering knowledge with research-backed innovation. The company delivers scalable solutions across digital engineering, data and analytics, cloud, and AI/ML sectors.

• Design, build, and optimize scalable data solutions on AWS using Databricks, including Lakehouse architectures based on Delta Lake and Unity Catalog;
• Develop and enhance batch and real-time data processing solutions using technologies such as Apache Spark, Flink, Kafka, Amazon MSK, and Kinesis;
• Lead data integration and migration activities, including source-to-target mapping, data ingestion, transformation, and quality assurance;
• Drive data platform architecture, data modeling, and engineering best practices to ensure scalability, reliability, and maintainability;
• Collaborate with business and technical stakeholders to translate requirements into effective data solutions, implementation roadmaps, and delivery plans;
• Support and mentor data engineering teams, define priorities, and promote technical excellence;
• Build and manage automated workflows and data pipelines using orchestration technologies such as Databricks Workflows, Apache Airflow, MWAA, Snowflake, and Amazon Redshift;
• Explore emerging technologies and share knowledge within the engineering community.

• Proven experience as a Lead Data Engineer in designing and delivering scalable data platforms and pipelines;
• Hands-on expertise in batch and real-time data processing using Apache Spark, Flink, Kafka, Amazon MSK, or Kinesis;
• Strong experience with AWS and Databricks, including Delta Lake, Unity Catalog, Workflows, and Jobs;
• Proficiency in Python, Scala, or Java, combined with advanced SQL skills;
• Experience building and orchestrating data workflows using Databricks Workflows, Apache Airflow, or MWAA;
• Practical knowledge of modern data warehousing and analytics solutions, including Snowflake and Amazon Redshift;
• Familiarity with data engineering best practices, version control, and data formats including Avro;
• Strong leadership, stakeholder management, and communication skills;
• English level: Upper-intermediate or higher;
• Nice to have: GitHub.

• Competitive, market-based pay;
• Health coverage;
• Paid time off;
• Wellness support;
• Learning opportunities;
• Access to advanced tech communities (AI/ML, Cloud, Quantum Computing, IoT, Robotics).