Senior Data Engineer

This is a fully remote position, open to applicants in Ukraine.

📋 Description

• Design, construct, and enhance production data pipelines and platforms on AWS.

• Develop scalable data processing solutions utilizing Spark/PySpark, Python, and SQL.

• Create and upgrade data lakes and lakehouse architectures leveraging Amazon S3, Apache Iceberg, AWS Glue, and associated services.

• Design, troubleshoot, and optimize analytical workloads and data warehouses, including Amazon Redshift and other OLAP platforms.

• Revamp legacy and inefficient data processes by transitioning ETL/ELT operations to scalable distributed data architectures.

• Engage with streaming and event-driven data pipelines using Kafka, Kinesis Data Firehose, and related technologies.

• Analyze production data issues and propose viable solutions.

• Manage customer projects from inception to completion, encompassing problem understanding, implementation, testing, and delivery.

• Collaborate directly with customers to clarify requirements, elucidate technical decisions, and suggest solutions.

• Establish data foundations for analytics and machine learning workloads in partnership with Data Scientists, DevOps, and MLOps engineers.

• Contribute to the development of dashboards and analytics using QuickSight or other business intelligence tools.

• Implement engineering practices related to data quality, testing, CI/CD, security, governance, and infrastructure automation.

⛳️ Requirements

• Proven experience in Data Engineering with a track record of independently managing and delivering data projects.

• Extensive hands-on experience with Apache Spark / PySpark and distributed data processing.

• Proficient in Python and SQL.

• Practical experience in creating data solutions on AWS.

• Strong knowledge of data lakes, lakehouse architectures, ETL/ELT processes, data modeling, and large-scale data processing.

• Familiarity with analytical databases and data warehouses.

• Significant experience with Amazon Redshift is highly desirable; extensive knowledge of Snowflake, Synapse, or comparable OLAP technologies is also relevant.

• Understanding of streaming architectures and technologies such as Kafka or Amazon Kinesis.

• Capability to troubleshoot existing data systems, comprehend upstream and downstream data flows, and enhance performance and reliability.

• Ability to work independently, make pragmatic technical choices, and assume accountability for delivery.

• Strong communication skills with the ability to discuss technical challenges and solutions directly with customers in English.

• Experience with Apache Iceberg or other modern open table formats and lakehouse technologies.

• Familiarity with Amazon OpenSearch Service / Elasticsearch.

• Experience with BI and visualization tools such as Amazon QuickSight, Tableau, or Power BI.

• Knowledge of Terraform and Infrastructure as Code.

• Familiarity with CI/CD practices for data pipelines, including data testing and validation.

• Experience in preparing data platforms for machine learning workloads using services such as Amazon SageMaker.

• Exposure to Amazon Bedrock, GenAI, or agentic development.

• Experience with Databricks, Snowflake, ClickHouse, or other modern data platforms.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible work environment and remote work options.

• Opportunities for professional development and continuous learning.

• Collaborative and inclusive company culture.

• Access to cutting-edge tools and technologies.