Contract Senior Data Engineer
New
Y
YLDData engineering
European Union (Remote); Source API remote eligibility restrictions: Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See (Vatican City State), Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Kosovo, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom, Åland IslandsContractSenior
Salary not disclosed
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Job Details
- Required Skills
- PythonApache AirflowKafkaSparkData modelingdbtAWS Lambda
Requirements
- Bring proven experience writing highly maintainable, performant Python code.
- Have experience building modern data pipelines using dbt, Kafka, Spark, AWS Kinesis, AWS Lambda, and Apache Airflow or similar.
- Understand data modelling patterns.
- Have deep knowledge of complex SQL, especially Common Table Expressions, window functions, and their performance.
- Have experience with end-to-end monitoring and alerting tools such as CloudWatch or Datadog.
- Balance innovative problem-solving with pragmatic technology choices for business needs.
- Be comfortable working in a dynamic production environment and managing client expectations.
- Have experience working closely with engineering leadership and architects.
- Demonstrate ownership and transparency in deliverables.
- The engagement is a B2B contract for an initial three months.
Responsibilities
- Build core infrastructure software, including data pipelines, APIs, and data models, as part of the client’s data platform team.
- Instrument systems for performance monitoring and ongoing enhancement.
- Provide data offerings to internal and external stakeholders using secure authentication patterns.
- Choose and implement technologies for scalable data access patterns.
- Implement batch processing and data streaming for soft real-time consumption.
- Apply knowledge of the client’s business domain when designing data solutions.
- Coach and mentor engineers to support their technical development.
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