Company Background

Our client is a global technology company transforming the way brands and agencies make marketing decisions. Its platform enables marketers to plan and activate cross-channel, programmatic media campaigns using real-time research, proprietary audience data, advanced analytics, and more than 150 integrated partners including Facebook, Instagram, Pinterest, Snapchat, and Twitter. The company operates across North America, Europe, the Middle East, Asia, and Australia.

Project Description

Data Management Platform is the core system that receives, processes and provides information to other external DMPs and real time platforms. The purpose of DMP is to store the connection between users/devices and their respective behavioral categories. Further this data is used by the other teams for the analytics and digital ad targeting. Team roadmap includes developing a new system based on the streaming architecture with a relevant tech stack.

Technologies

• Spark
• Scala
• Vertica
• Kafka
• Airflow
• K8S
• Python, Java (preferable)

What You'll Do

• Own end-to-end development, from design to production, with a focus on innovation and efficiency;
• Lead and mentor developers on complex projects impacting core business systems;
• Contribute to the design and development of next-generation data solutions;
• Implement high-scale big data solutions and contribute to platform infrastructure and architecture;
• Research and evaluate core technologies, integrations, and external APIs;
• Collaborate with cross-functional stakeholders, including Product, Engineering, and data providers;
• Participate in an off-hours pager duty rotation;

Job Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, or equivalent experience;
• 4+ years of software development experience;
• 2+ years of experience with Apache Spark;
• 2+ years of experience with Scala (preferred) and/or Python or Java;
• Experience working with high-performance, large-scale, or distributed data systems;
• Experience with SQL and NoSQL databases;
• Experience with Kubernetes;
• Experience with Git;
• Experience building and optimizing data pipelines, ETL processes, and streaming systems (e.g., Hadoop, Spark, Kafka) is a plus;
• Familiarity with tools such as GitLab, Grafana, InfluxDB, and Kibana is a plus;
• Strong communication skills and ability to work effectively in a team;
• English level: B1+ or higher;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Project Description

We are looking for an experienced Data Engineer with deep expertise in Databricks to join our advanced analytics and data engineering team. The ideal candidate will play a key role in designing, building, and optimizing large-scale data solutions on the Databricks platform, supporting business intelligence, advanced analytics, and machine learning initiatives. You will collaborate with cross-functional teams to deliver robust, scalable, and high-performance data pipelines and architectures.

Technologies

• Databricks (including Spark, Delta Lake, MLflow)
• Python/Scala
• SQL
• ETL concepts
• Distributed data processing
• Data warehousing
• Cloud Platforms & Storage

What You'll Do

• Lead the design, development, and deployment of scalable data pipelines and ETL processes using Databricks (Spark, Delta Lake, MLflow);
• Architect and implement data lakehouse solutions, ensuring data quality, governance, and security;
• Optimize data workflows for performance and cost efficiency on Databricks and cloud platforms (Azure, AWS, or GCP);
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights;
• Mentor and guide junior engineers, promoting best practices in data engineering and Databricks usage;
• Develop and maintain documentation, data models, and technical standards;
• Monitor, troubleshoot, and resolve issues in production data pipelines and environments;
• Stay current with emerging trends and technologies in data engineering and Databricks ecosystem;

Job Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field;
• 5+ years of experience in data engineering, with at least 2 years of hands-on experience with Databricks (including Spark, Delta Lake, and MLflow);
• Strong proficiency in Python and/or Scala for data processing;
• Deep understanding of distributed data processing, data warehousing, and ETL concepts;
• Experience with cloud data platforms (Azure Data Lake, AWS S3, or Google Cloud Storage);
• Solid knowledge of SQL and experience with large-scale relational and NoSQL databases;
• Familiarity with CI/CD, DevOps, and infrastructure-as-code practices for data engineering;
• Experience with data governance, security, and compliance in cloud environments;
• Excellent problem-solving, communication, and leadership skills;
• English: Upper Intermediate level or higher;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

Sep 25, 2025 12:50