Time since we first saw it
Day 0
Early. Similar jobs usually come down between day 5 and day 54.
From 10,704 similar postings that came down. Coming down is not always a hire.
Warsaw, Poland
Actively hiring, first seen by us todayWork setup in the employer’s posting: RemoteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Develop and maintain batch and near real-time data pipelines
Transform, validate and optimize data using Databricks, PySpark and SQL
Build, test and automate ETL processes and data workflows
Support Data Lakehouse implementation following engineering standards
Troubleshoot, optimize and monitor data pipelines
Develop and maintain data pipelines for processing large volumes of data in batch and near real-time environments
Work with Databricks, PySpark, and SQL to transform, validate, and optimize data
Build, test, and automate ETL processes and data workflows
Support implementation of Data Lakehouse solutions following engineering standards and best practices
Troubleshoot, optimize, and monitor data pipelines
2+ years of experience in Big Data development and database design
Strong hands-on experience with SQL
Strong Python development skills
Hands-on experience with PySpark
Experience developing and maintaining data pipelines in Databricks
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 0
Early. Similar jobs usually come down between day 5 and day 54.
From 10,704 similar postings that came down. Coming down is not always a hire.
35 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Strong hands-on experience with SQL - Strong Python development skills - Hands-on experience with PySpark
The project focuses on developing and supporting scalable Data Lakehouse solutions for processing large volumes of marketing and advertising data. The team works with batch and near real-time data pipelines, cloud-native infrastructure, and modern big data technologies. Key Technologies: Databricks, PySpark, Python, SQL, Delta Lake, Medallion Architecture, ETL Pipelines, AWS S3
- Develop and maintain data pipelines for processing large volumes of data in batch and near real-time environments - Work with Databricks, PySpark, and SQL to transform, validate, and optimize data - Support implementation of Data Lakehouse solutions following engineering standards and best practices
- 2+ years of experience in Big Data development and database design - Strong hands-on experience with SQL - Strong Python development skills
WILL BE A PLUS - Experience with AWS services, including S3 Company Description
- Hands-on experience with PySpark - Experience developing and maintaining data pipelines in Databricks - Experience with Delta Lake
We are looking for a Middle Data Engineer to join our team and contribute to building scalable data solutions for a leading AdTech and analytics company. In this role, you will work with modern Data Lakehouse architecture, high-load distributed systems, and cloud-native technologies while helping process large volumes of marketing and advertising data in batch and near real-time environments. This is an excellent opportunity for engineers who want to deepen their expertise in Databricks, PySpark, Delta Lake, and scalable data platforms while collaborating with experienced data engineering professionals on enterprise-scale solutions. About Sigma Software: Sigma Software is a global IT consulting company delivering software development and IT consulting services to clients worldwide across multiple industries.
- Experience developing and maintaining data pipelines in Databricks - Experience with Delta Lake - Experience with Medallion Architecture (Bronze, Silver, Gold layers)
- Strong Python development skills - Hands-on experience with PySpark - Experience developing and maintaining data pipelines in Databricks
Complete your application on jobs.smartrecruiters.com. The employer’s form will show what is required.
Already applied? Track this application
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
WILL BE A PLUS
We are looking for a Middle Data Engineer to join our team and contribute to building scalable data solutions for a leading AdTech and analytics company. In this role, you will work with modern Data Lakehouse architecture, high-load distributed systems, and cloud-native technologies while helping process large volumes of marketing and advertising data in batch and near real-time environments.
This is an excellent opportunity for engineers who want to deepen their expertise in Databricks, PySpark, Delta Lake, and scalable data platforms while collaborating with experienced data engineering professionals on enterprise-scale solutions.
About Sigma Software: Sigma Software is a global IT consulting company delivering software development and IT consulting services to clients worldwide across multiple industries.
CUSTOMER
Our customer is a leading AdTech and data analytics company specializing in high-load platforms for large-scale data processing and analytics. The company develops cloud-based solutions that help businesses manage data, build analytical models, and generate actionable insights for marketing and advertising operations.
The customer operates globally and focuses on scalable microservices architecture, modern engineering practices, and enterprise-grade analytics platforms.
PROJECT
The project focuses on developing and supporting scalable Data Lakehouse solutions for processing large volumes of marketing and advertising data. The team works with batch and near real-time data pipelines, cloud-native infrastructure, and modern big data technologies.
Key Technologies: Databricks, PySpark, Python, SQL, Delta Lake, Medallion Architecture, ETL Pipelines, AWS S3
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Warsaw, Poland
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.