This is a remote position.

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  Analyzes complex customer data to determine integration needs.
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  Develops and tests scalable data integration/transformation pipelines using PySpark, SparkSQL, and Python.
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  Contributes to the codebase through coding, reviews, validation, and complex transformation logic.
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  Automates and maintains data validation and quality checks.
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  Collaborates with FPA, data engineers, and developers to align solutions with financial reporting and business objectives.
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  Participates in solution architecture and technical discussions, refining user stories and acceptance criteria.
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  Utilizes modern data formats/platforms (Parquet, Delta Lake, S3/Blob Storage, Databricks).
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  Partners with the product team to ensure accurate customer data reflection and provide feedback based on data insights.

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  A Data Analytics Engineer with 5+ years of experience.
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  Must have strong Python, PySpark, Notebook, and SQL coding skills, especially with Databricks and Delta Lake.
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  Proven ability to build and deploy scalable ETL pipelines to cloud production environments using CI/CD.
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  Experience with Agile/Scrum, data quality concepts, and excellent communication is essential.
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  Cloud environment (Azure, AWS) and Infrastructure as Code (Terraform, Pulumi) experience beneficial.
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  Telecoms industry or consulting experience, plus accounting knowledge, is a plus.

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  J106998

Requirements