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  Build and optimize data models and ETL pipelines for enterprise reporting and analytics.
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  Work with Snowflake, dbt, and Airflow to create robust, cost-efficient data flows.
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  Define best practices in data governance, data quality, and warehouse optimization.

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  Develop and maintain large-scale data and ML pipelines using Spark, Hadoop, and AWS.
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  Write efficient and scalable code in Java or Scala, integrating multiple data sources.
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  Optimize data processing for high-volume, complex datasets and analytics workloads.

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  Build real-time data ingestion and low-latency streaming pipelines.
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  Work with Kafka, Flink, and Spark Streaming to enable real-time decision systems.
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  Deploy and orchestrate services in Docker / Kubernetes environments.

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  Design and implement cloud-native data architectures using AWS, Azure, or GCP.
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  Integrate security, automation, and CI/CD pipelines into data workflows.
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  Collaborate with clients globally on data modernization and migration projects.

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  Build, test, and maintain scalable data pipelines and analytical platforms.
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  Ensure data reliability, quality, and performance through automated monitoring and testing.
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  Integrate diverse data sources using ETL, ELT, and streaming techniques.
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  Apply DevOps practices to data solutions (Terraform, CloudFormation, Docker, Kubernetes).
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  Partner with data scientists, architects, and business stakeholders to deliver impactful solutions.

Requirements

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  Minimum 5 years of professional experience in data engineering or related field.
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  Strong programming skills in Python, Java, or Scala.
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  Excellent SQL and data modeling expertise.
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  Hands-on experience with Big Data frameworks (Spark, Hadoop, Flink, Beam).
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  Knowledge of data orchestration tools (Airflow, Prefect, Control-M).
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  Experience with streaming systems (Kafka, Pub/Sub).
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  Solid understanding of cloud platforms (AWS, GCP, Azure) and native data services (S3, Redshift, BigQuery, Dataproc).
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  Familiarity with containerization and CI/CD (Docker, Kubernetes, Jenkins).
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  Strong analytical and problem-solving mindset.
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  Very good command of English (B2 minimum).

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  Experience with dbt, Databricks, Terraform, or Data Governance frameworks.
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  Knowledge of industry standards such as NIST SSDF, ISO 27001, or data privacy frameworks.
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  Certifications in AWS / Azure / GCP or data engineering specializations.

Benefits

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  Multisport card and MyBenefit program;
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  Medical care;
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  Language courses;
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  Career in the multinational company;
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  Opportunity to take part in international projects and gain experience with various businesses;
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  Set of social benefits to choose from;
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  Training program.