Data Engineer İş İlanı

As Turkiye's largest fitness community—bringing together our MAC/One, MACFit, MAC Studio, and NuSpa brands—we are looking for a Data Engineer to join our Technology team at our Ortaköy Head Office in Istanbul. Being part of MAC means being a core piece of a continuously growing, dynamic community that moves together for a better life. Here, ideas are valued, teammanship is deeply supported, and feeling good is just as important as working efficiently. If you want to be a part of our well-being community and shape the future of the fitness experience through data technologies, we would love to hear from you! Qualifications & Experience We Are Looking For • Education: Bachelor’s degree (Master’s preferred) in Computer Engineering, Software Engineering, Mathematical Engineering, Industrial Engineering, or related fields. • Experience: Minimum 4 years of experience in data engineering, with a proven track record in developing and managing data pipelines and data warehouses. • Database & ETL: Strong experience with Oracle Data Integrator (ODI) and Oracle databases (SQL, PL/SQL). Hands-on expertise in analyzing, developing, and optimizing complex ETL processes. • Core Languages & Platforms: Advanced SQL and strong Python skills. Experience with at least one modern analytical data platform such as BigQuery, Snowflake, ClickHouse, or Apache Doris . • Cloud Infrastructure: Practical experience with Google Cloud Platform (GCP)—specifically BigQuery, Cloud Storage, Cloud Run, and Pub/Sub . • Data Modeling: Proficiency in data modeling, dimensional modeling, star schema, and slowly changing dimensions (SCD). • Orchestration & Transformation: Experience with workflow management and transformation tools such as Airflow, dbt, or Dataform . • Integration: Proven experience in integrating data from disparate systems using API and CDC (Change Data Capture) methods. • Data Quality & CI/CD: Knowledge of data quality frameworks, testing, monitoring, and CI/CD pipeline implementation. • AI/ML Support: Experience with data pipelines, training datasets, and infrastructure supporting machine learning models. • BI & Documentation: Ability to build reliable, well-documented datasets to support Power BI reporting. • Cost Optimization: Knowledge of optimizing storage, processing, and query costs in cloud environments. • Communication & Mindset: • Strong communication skills in both English and Turkish. • Excellent analytical thinking and problem-solving capabilities. • Ability to translate complex technical concepts and options into clear insights for non-technical stakeholders. • Collaborative approach and strong team player mindset. What Will You Be Doing? • Analyze and optimize our existing Oracle/ODI-based data warehouse and actively contribute to modernizing our data architecture. • Build and maintain scalable, reliable data pipelines for incoming data across membership, CRM, finance, mobile, web, and marketing platforms. • Leverage GCP tools ( BigQuery, Cloud Run, Vertex AI ) to build data infrastructures supporting reporting, analytics, machine learning, and AI initiatives. • Design, build, and optimize both batch and incremental data processing pipelines. • Develop robust data models and data marts that allow business units to track key performance indicators (KPIs) consistently. • Collaborate closely with Data Science and AI Engineering teams to prepare data sets and pipelines required for AI and machine learning applications. • Establish data infrastructure for model development, training, deployment, and monitoring. • Enhance platform reliability by implementing automated data quality, testing, and monitoring workflows. • Prepare clean, accessible, and well-documented data layers for self-service Power BI reporting. • Collaborate with internal teams and third-party tech partners to ensure technical standards, control deliverables, and retain core domain knowledge in-house. • Ensure high performance, scalability, and cost optimization as data volume grows. • Contribute to architectural and technical decision-making to keep the infrastructure aligned with evolving business needs. • Continuously follow emerging trends in data engineering and cloud technologies to elevate MAC’s data ecosystem. Nice-to-Haves • Experience in data warehouse modernization or legacy migration projects. • Hands-on experience with MLOps processes (Feature Store, Vertex AI Pipelines, model deployment, and monitoring). • Experience with streaming or real-time data processing. • Proficiency in Power BI or SSAS Tabular. • Knowledge of GA4, event-based product analytics, and customer engagement platforms. • Prior experience in high-data-volume sectors such as tech, retail, consumer products, or fitness/wellness.