Über
We are looking for an experienced Data Architect to design and manage scalable, secure, and high-performance data solutions. The candidate will drive enterprise data architecture, define data models, and build end-to-end frameworks for data integration, governance, and analytics across multiple platforms.
Responsibilities
Collaborate with client stakeholders to gather requirements, structure problems, and ensure high-quality, timely delivery. Experience working hands-on in the Databricks tech stack with strong proficiency in SQL, Python, and PySpark Build, orchestrate, and monitor scalable data pipelines on Databricks, ensuring reliable ingestion, transformation, CDC handling, and incremental load strategies. Manage end-to-end pipeline operations including performance tuning, data quality monitoring, alerting, and issue resolution across production workloads. Design and optimize data models, marts, and Lakehouse/warehouse layers with strong focus on medallion architecture, query optimization, and performance engineering. Lead a project team of 5 - 10 data engineers supporting multiple workstreams and provide technical leadership through code reviews, best-practice guidance, reusable pattern creation, and mentorship to engineering team members. Qualifications
Qualifications (Required):
Bachelor's or Master's degree in economics, mathematics, computer science/engineering, operations research or related analytics areas Demonstrated leadership ability and willingness to take initiative Entrepreneurial hands-on approach to work Superior analytical and problem solving skills Outstanding written and verbal communication skills Effective time management and attention to detail 6-10 years' experience in data analytics or data engineering role Hands on experience in using SQL, Python and Workflow Schedulers (Apache Airflow, Cron) Experience in leading team and coordinating with internal / external stakeholders Qualifications (Preferred):
Experience in using Cloud Platforms (AWS / GCP / Azure) Experience in using Visualization tools (Tableau / Power BI) Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.)
Sprachkenntnisse
- English
Hinweis für Nutzer
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