Data Engineer

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.
• 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.