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Analytics Engineer

Hybrid - Full Time - Data Platform

Cyprus

Application ID: 1472

The Data Usage team is responsible for building and maintaining data pipelines and a centralized Data Warehouse (DWH) at inDrive, based on Google Cloud Platform.


Our mission is to ensure:

  • correctness and completeness of data,
  • compliance of the DWH with audit requirements,
  • transparency and trust in data for business and finance stakeholders.

We are looking for a Middle Analytics Engineer with hands-on experience working with data warehouses, who understands DWH architecture, incremental data processing, and the responsibility that comes with financial data.


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Key Responsibilities

  • Gather and clarify requirements from analytics and finance stakeholders
  • Design and evolve DWH architecture (ODS / Data Marts) with audit requirements in mind
  • Develop and maintain financial data pipelines
  • Design, implement, and support incremental data pipelines
  • Develop and optimize data marts in BigQuery (Dataform)
  • Analyze source systems and build data flows from source to consumption
  • Maintain and develop workflows in Airflow
  • Participate in testing, data validation, and release processes
  • Investigate data quality issues and financial discrepancies
  • Maintain technical documentation required for audit and data governance

Skills, Knowledge and Expertise

  • 2–3+ years of experience as an Analytics Engineer / DWH Engineer / Data Analyst working with DWH
  • Hands-on experience with data warehouses
  • Strong understanding of DWH architecture and data layers (ODS, Data Marts)
  • Understanding of incremental loads, historical data handling, and deduplication
  • Strong SQL skills
  • Experience designing and optimizing data marts
  • Experience with BigQuery (partitioning, clustering, cost-aware querying)
  • Experience with Airflow or similar orchestration tools
  • Python for data processing and ETL tasks
  • Ability to work with stakeholders and translate business needs into data requirements

Must have to be familiar with:

• Languages: SQL (strong knowledge), Python (basic knowledge)
• Orchestration: Airflow or similar orchestration tool
• Version Control: Git
• Experience with Data Quality / Data Governance / SLAs

Nice but not mandatory to be familiar with:

  • Cloud & Storage: Google Cloud Platform (BigQuery, Dataform, Cloud Storage)
  • Streaming: Kafka-based data delivery pipelines (streaming, schemas, delivery guarantees)
  • Processing frameworks: Spark, Apache Beam
  • Analytics & BI: Looker, Tableau
  • Experience working with financial data or financial reporting
  • Experience preparing data for audits or regulatory requirements

Conditions & Benefits

  • Modern cloud technical stack
  • Real impact on data architecture and processes
  • Flexible work schedule and format
  • Health insurance
  • Learning and professional development support
  • Access to psychological, financial, and legal support programs

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