Senior Data Engineer

🕒 September 10

🇺🇦 Ukraine – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 11%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Automat-it

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Automat-it is an all-in AWS Premier partner empowering startups with DevOps & FinOps expertise and hands-on services. Founded in 2012 by CEO Ziv Kashtan, Automat-it has guided and supported hundreds of startups to leverage AWS smarter throughout their growth journey. Specializing in DevOps, Cloud services, DBA, IT infrastructure, and Performance, they build cloud solutions from the DevOps perspective to optimize cloud performance and economics for their customers.

📋 Description

• Design, build, and optimize production data pipelines and data platforms on AWS • Build scalable data processing workloads using Spark/PySpark, Python, and SQL • Build and modernize data lakes and lakehouse architectures using Amazon S3, Apache Iceberg, AWS Glue, and related services • Design, troubleshoot, and optimize analytical workloads and data warehouses, including Amazon Redshift and other OLAP platforms • Modernize legacy and inefficient data workloads by moving ETL/ELT processing to scalable distributed data architectures • Work with streaming and event-driven data pipelines using Kafka, Kinesis Data Firehose, and related services • Investigate production data problems and recommend practical solutions • Own customer projects end-to-end, from understanding technical problems through implementation, testing, and delivery • Work directly with customers to clarify requirements, explain technical decisions, and recommend solutions • Build data foundations for analytics and ML workloads with Data Scientists, DevOps, and MLOps engineers • Contribute to dashboards and analytics using QuickSight or other BI tools • Apply engineering practices around data quality, testing, CI/CD, security, governance, and infrastructure automation

🎯 Requirements

• Strong production experience in Data Engineering, with the ability to independently own and deliver data projects • Deep hands-on experience with Apache Spark / PySpark and distributed data processing • Strong Python and SQL skills • Hands-on experience building data solutions on AWS • Strong understanding of data lakes, lakehouse architectures, ETL/ELT, data modeling, and data processing at scale • Experience with analytical databases and data warehouses • Strong Amazon Redshift experience is highly valuable; deep experience with Snowflake, Synapse, or similar OLAP technologies is also relevant • Understanding of streaming architectures and technologies such as Kafka or Amazon Kinesis • Ability to troubleshoot existing data systems, understand upstream and downstream data flows, and improve performance and reliability • Ability to work autonomously, make pragmatic technical decisions, and take responsibility for delivery • Good communication skills and ability to discuss technical problems and solutions directly with customers in English • Experience with Apache Iceberg or other modern open table formats and lakehouse technologies • Amazon OpenSearch Service / Elasticsearch experience • Experience with BI and visualization tools such as Amazon QuickSight, Tableau, or Power BI • Terraform and Infrastructure as Code • CI/CD practices for data pipelines, including data testing and validation • Experience preparing data platforms for ML 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