WHO WE ARE:

We are a full-Service agency & content Studio helping companies to thrive through strategy, creative, technology services, and human talent.

REQUIRED SKILLS AND EXPERIENCE:

• 5+ years of experience in data engineering or a similar role.
• Strong hands-on experience with GCP services including Dataflow, Pub/Sub, BigQuery, and Cloud Data Fusion.
• Proficiency in building stream processing systems using Kafka.
• Familiarity with Docker, Kubernetes, and cloud services (AWS, GCP).
• Advanced knowledge of Python and Linux shell scripting.
• Proven expertise in streaming data architectures and real-time processing.
• Experience ingesting and integrating data from on-premise sources, data lakes, and streaming platforms.
• Experience with business intelligence software (e.g., Power BI, Tableau) and the graphic display of quantitative data.
• Proficient in Python and SQL for data manipulation, transformation, and automation.
• Skilled in pipeline orchestration tools such as Airflow, Cloud Composer, or equivalent.
• Solid understanding of data modeling, data governance, and performance optimization best practices.

JOB PURPOSE:

We’re looking for a Senior Data Engineer with deep expertise in building scalable, efficient, and secure data pipelines on Google Cloud Platform (GCP). You will play a key role in designing and implementing robust data solutions that empower data-driven decisions across the organization.
If you have a passion for cloud-native architectures, streaming data, and modern data integration strategies, we’d love to talk.

KEY RESPONSIBILITIES:

• Design, build, and maintain data pipelines using Dataflow, Cloud Pub/Sub, BigQuery, and Cloud Data Fusion.
• Develop scalable streaming and batch pipelines to support real-time and historical data use cases.
• Lead data ingestion efforts from on-premise systems, data lakes, and external APIs into the cloud environment.
• Collaborate with data scientists, analysts, and platform teams to ensure data availability and quality.
• Write efficient and production-grade Python and SQL code for data transformation and validation.
• Implement pipeline orchestration using tools such as Cloud Composer, Airflow, or similar.
• Monitor, troubleshoot, and optimize data pipelines to ensure performance and reliability.
• Contribute to architecture and design decisions that support long-term scalability and maintainability.