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Tech Stack
Tools & technologiesAzureETLJavaPythonScalaSparkSQL
About the role
Key responsibilities & impact- Design, develop, and maintain ETL and data transformation processes
- Implement and support Spark-based data pipelines
- Contribute to data integration initiatives across the platform
- Analyze and troubleshoot data-related issues
- Ensure data quality, reliability, and performance across systems
- Work closely with functional and technical stakeholders to gather and analyze requirements
- Collaborate in Agile teams and contribute to continuous improvement of data solutions
- Participate in DevOps practices and CI/CD processes
Requirements
What you’ll need- 3+ years of experience in data engineering or software development
- Strong SQL knowledge (ANSI SQL, Hive SQL, Spark SQL)
- Hands-on experience with Spark
- Programming experience in at least one of the following: Scala, Python, or Java
- Experience with Big Data environments such as Azure Databricks, Amazon EMR, Hive, or Cloudera
- Familiarity with DevOps and CI/CD practices (Git, GitHub, Sonar, Nexus)
- Ability to work effectively in Agile teams
- Strong analytical skills and ability to collaborate with cross-functional teams
- English proficiency level: B2 or higher
Benefits
Comp & perks- Career development opportunities
- Training opportunities to develop new skills in finance, technology, and data management
- Chance to work in a challenging, multicultural environment with international projects
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
ETLdata transformationSparkSQLANSI SQLHive SQLSpark SQLScalaPythonJava
Soft Skills
analytical skillscollaborationcommunicationAgile teamworkproblem-solving