Data Engineer

Mars Athletic Club; Beşiktaş; Vor Ort; TRY 420.000 - 640.000; Vollzeit

Zusammenfassung

Mars Athletic Club invites applications for a Data Engineer to join the Technology team at our Ortaköy Head Office in Istanbul. The role focuses on modernizing our data architecture, building scalable data pipelines across multiple platforms, and supporting analytics and ML initiatives.

You will work with ODI/Oracle, BigQuery, Airflow, and a range of cloud tools to deliver reliable data services, data models, and BI-ready datasets. Strong English and Turkish communication is required.

Qualifikationen

• Bachelor’s degree (Master’s preferred) in relevant engineering fields.
• Minimum 4 years of data engineering experience with data pipelines and data warehouses.
• Strong ODI and Oracle SQL/PLSQL experience with ETL optimization.
• Advanced SQL and Python; experience with major analytical data platforms (BigQuery/Snowflake/ClickHouse/Doris).
• GCP experience with BigQuery, Cloud Storage, Cloud Run, Pub/Sub.
• Proficient data modeling (star schema, SCD).
• Experience with Airflow, dbt, or Dataform.
• Data integration from APIs and CDC.
• Knowledge of data quality, testing, monitoring, and CI/CD.
• Experience supporting AI/ML pipelines and Power BI data readiness.
• Excellent English and Turkish communication; strong stakeholder skills.
• Ability to translate technical concepts for non-technical audiences.

Aufgaben

• Analyze and optimize our Oracle/ODI-based data warehouse and modernize data architecture.
• Build and maintain scalable data pipelines across membership, CRM, finance, mobile, web, and marketing.
• Leverage GCP tools (BigQuery, Cloud Run, Vertex AI) for data infrastructure supporting analytics and ML.
• Design and optimize batch and incremental data processing pipelines.
• Develop data models and data marts for consistent KPI tracking.
• Collaborate with Data Science/AI teams to prepare datasets for ML.
• Establish data infrastructure for model development, training, deployment and monitoring.
• Enhance platform reliability with automated data quality, testing, and monitoring.
• Prepare clean, documented data layers for Power BI reporting.
• Collaborate with internal teams and partners to maintain technical standards.
• Ensure performance, scalability and cost optimization as data grows.
• Contribute to architectural decisions aligning with business needs.
• Stay updated on data engineering and cloud tech trends.

Kenntnisse

SQL

Python

Analytical thinking

Team player

English/Turkish communication

Ausbildung

Bachelor’s degree in Computer Engineering/Software Engineering/related fields

Tools

ODI

Oracle databases (SQL/PLSQL)

BigQuery

Snowflake

ClickHouse

Apache Doris

Airflow

dbt

Dataform

GCP (Cloud Run, Pub/Sub, Cloud Storage)

Jobbeschreibung

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.