Senior Data Engineer & Analyst

Required skills

Requirements

6+ years of data engineering experience
2+ years of Google Cloud Platform experience (BigQuery, Cloud Composer, Cloud Storage, Dataflow, DataStream)
Experience with programming languages and frameworks, including SQL and Python
Proficiency with workflow orchestration tools (Airflow, Cloud Composer)
Experience with real-time and streaming data technologies (Pub/Sub, Kafka, Spark)
Experience with building, versioning, and deploying production-grade data pipelines
Ability to optimize queries and data models for large-scale analytical workloads
Deep knowledge of data pipeline performance tuning and reliability practices
Deep understanding of data modeling, semantic layers, and analytics enablement
Ability to work in agile environments with iterative delivery and cross-functional teams
Strong communication skills in both spoken and written English
Bachelor's Degree in Computer Engineering, Computer Science, or equivalent

Lead data engineering and analytics initiatives with a focus on data engineering and analytics delivery
Design and evolve scalable data platforms and cloud-based data architectures
Build, deploy, and maintain batch and streaming data pipelines across cloud environments
Apply business logic to semantic data models to enable self-service analytics and reporting
Optimize data pipelines for performance, scalability, reliability, and cost efficiency
Implement and maintain CI/CD workflows for automated deployment of data pipelines and data products
Define, monitor, and improve data quality, data consistency, and data reliability standards
Capture and maintain data lineage, metadata, and documentation to support governance and transparency
Develop and maintain RESTful APIs to expose curated datasets and data services
Troubleshoot data pipeline failures and perform root-cause analysis with long-term remediation
Collaborate with business stakeholders, analytics, IT, and data science teams to translate requirements into data solutions
Mentor junior engineers through technical guidance, code reviews, and best practices
Ensure compliance with security, privacy, and organizational standards across data workflows

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