Senior data engineer – data quality & platform ownership (latam or europe)
at cloudgeometry, we have embarked on the mission to truly offer top-notch, cloud-first, ai-driven technology solutions to our customers. We are an aws-advanced consulting partner, cncf member, and kubernetes certified service provider, part of the ai&data working group under the linux foundation. We work for enterprise us fortune 500 companies and tech start-ups from silicon valley to europe. While working on our projects, you are not going to just disappear from the company radar, as we are all engineering-driven, so do expect a question or request for engagement even from our ceo.
if you're looking to elevate your career, be part of silicon valley start-ups, and contribute to next-generation businesses in innovative financial and social apps, this is the place for you.
about the role:
now we are looking for a hands-on senior data engineer to overhaul our databricks-based data infrastructure and establish robust data quality frameworks. In this key role, you will design and implement scalable data pipelines, develop error handling and alerting systems, and enforce engineering best practices to ensure a high-performing and reliable data ecosystem.
core responsibilities
process improvement
* review and redesign data ingestion pipelines (with schema validation, duplicate detection, automated encoding correction, missed data enrichment, etc.)
* implement end-to-end data quality checks and monitoring (great expectations, dbt, deequ, monte carlo, apache airflow, etc.)
* improve ci/cd pipelines with unit/integration testing, code reviews, and deployment rollback capabilities
* participate in engineering tasks like pull request reviews and documentation templates
error handling & reliability engineering
* develop fault-tolerant pipelines with retry mechanisms, dead-letter queues, and checkpointing
* create centralized error taxonomy and logging and severity-based alerts
* implement data lineage tracking (openlineage, marquez) for root cause analysis of quality issues
* conduct post-mortems for critical failures and maintain sla/slo
required skills:
* 5+ years building production-grade data pipelines and implementing data quality frameworks (spark, python, sql)
* expert in databricks (delta lake, cdc, workflows, unity catalog) and aws integrations
* proven experience with data observability tools
* deep knowledge of distributed systems failure modes and recovery patterns
* ability to balance strategic planning with tactical firefighting
* exceptional communication skills for bridging engineering/data science teams
* bs/ms in computer science or equivalent
* databricks certified professional or aws/azure data engineering certs
we are building hyper-growth careers in cloud native, ai/ml-centric projects, using the best silicon valley practices, anywhere in the world.
* remote anywhere.
* b2b with multiple benefits.
* paid days off annually.
* workspace program: $2500 for work equipment of your choice.
* english language lessons on all levels.
* performance financial incentives for the people who demonstrate interest in the company’s development.
* paid courses and certifications: for example aws, cka, ml certifications.
* participation at international conferences: like cncf summits, kubecon, others.
seniority level
executive
employment type
full-time
job function
information technology
industries
it services and it consulting
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