
IT Data Platform Engineer
12 hours ago
- Design, develop, and maintain data pipelines to extract, transform, and load (ETL) data from various sources into our data warehouse or data lake environment.
- Automate, manage, and scale the underlying infrastructure for our data platforms (e.g., Airflow, Spark clusters), applying SRE and DevOps best practices for performance, reliability, and observability.
- Collaborate with stakeholders to gather requirements and translate business needs into robust technical and platform solutions.
- Optimize and tune existing data pipelines and infrastructure for performance, cost, and scalability.
- Implement and enforce data quality and governance processes to ensure data accuracy, consistency, and compliance with regulatory standards.
- Work closely with the BI team to design and develop dashboards, reports, and analytical tools that provide actionable insights to stakeholders.
- Mentor junior members of the team and provide guidance on best practices for data engineering, platform development, and DevOps.
- (Nice-to-have) Aptitude for proactively identifying and implementing GenAI-driven solutions to achieve measurable improvements in the reliability and performance of data pipelines or to optimize key processes like data quality validation and root cause analysis for data issues.
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 3+ years of experience in data engineering, platform engineering, or a similar role, with a strong focus on building and maintaining data pipelines and the underlying infrastructure.
- Must have proven experience in a DevOps, SRE, or System Engineering role, with hands-on expertise in infrastructure as code (e.g., Terraform, Ansible), CI/CD pipelines, and monitoring/observability tools.
- Expertise in SQL programming and database management systems (e.g., BigQuery).
- Hands-on experience with ETL tools and technologies (e.g., Apache Spark, Apache Airflow).
- Experience with cloud platforms such as Google Cloud Platform (GCP), and experience with relevant services (e.g., GCP Dataflow, GCP DataProc, BigQuery, Cloud Composer, GKE).
- Experience with Big Data tools like Spark, Kafka, etc.
- Experience with object-oriented/object function scripting languages: Python/Scala, etc.
- (Nice-to-have) Demonstrated readiness to leverage GenAI tools to enhance efficiency within the typical stages of the data engineering lifecycle, for example by generating complex SQL queries, creating initial Python/Spark script structures, or auto-generating pipeline documentation.
- (Plus) Experience with BI tools and visualization platforms (e.g., Tableau).
- (Plus) Experience with SAP HANA, SAP BW, SAP ECC, or other SAP modules.
- Strong analytical and problem-solving skills, with the ability to analyze complex data sets and derive actionable insights.
- Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
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