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Scala Data Engineer Lead

2 weeks ago

Budapest, Budapest, Czech Republic beBee Careers Full time

Job Summary

We are seeking a highly skilled Scala Data Engineer Lead to join our team. The ideal candidate will have extensive experience in designing and developing data engineering solutions, including data pipelines and ETL processes.

Key Responsibilities

  • Leverage technical expertise to lead the design and development of data engineering solutions.
  • Mentor and lead a team of data engineers, providing guidance and oversight for high-quality deliverables.
  • Evaluate team performance, provide feedback and coaching, and encourage collaboration and open communication within the team and with stakeholders.

Requirements

  • Strong technical skills in code review, architecture, and data models.
  • Experience designing data pipelines and building ETL processes.
  • 6+ years of proven experience developing software using Scala/Java.
  • Proficiency in SQL and query tuning.
  • Solid understanding of distributed computing approaches, patterns, and technologies (Spark, Kafka).
  • Deep knowledge of data warehousing principles and modeling concepts (OLTP/OLAP, normalization, dimensional, star).
  • Experience working with cloud platforms (GCP, AWS, Azure).
  • Experience in modern data warehouse building using tools like Snowflake, AWS Redshift, and BigQuery.
  • Expertise in relational databases (PostgreSQL, MSSQL, MySQL).
  • Experience with orchestration tools for data flows (Apache Airflow, Talend, Glue, Azure Data Factory).

Benefits

  • Competitive compensation package.
  • Stable employment based on a full-time employment contract.
  • Private health insurance.
  • AYCM sport pass, providing discounts at various sports facilities.
  • Interesting tasks and diverse opportunities for developing your skills.
  • Free training courses.
  • Participation in internal and external thematic events and technical conferences.
  • A spacious office in Budapest.
  • All necessary devices and tools for your work.
  • Active corporate life.

Others

  • The ideal candidate will stay up-to-date with industry best practices and emerging technologies.
  • Experience with non-relational databases (MongoDB, DynamoDB), data lakes and lake houses (Azure Data Lake, Apache Hudi, Apache Iceberg, Delta Lake), stream processing (AWS Kinesis, Kafka streams), containerized or serverless deployment (Docker, ECS, Kubernetes, Lambda).
  • Familiarity with popular data standards and formats (JSON, XML, Proto, Parquet, Avro, ORC) and experience with Informatica, Databricks, Talend, Fivetran, or similar.
  • Knowledge of machine learning models and experience in data science and machine learning is a plus.