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Sr Data Platform Engineer / Platform Lead - Digital Products _Reading,PA_Fulltime

Keylent Inc.
Reading, PA, United States
2 days ago
Apply on www.dice.com
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours
Job source
www.dice.com

Tech stack

Sql Data Warehouse Airflow Amazon Web Services Amazon S3 Confluence Big Data Software as a Service Cloud Database Cloud Storage Continuous Delivery Continuous Integration Information Engineering
+37 more
Data Governance Data Infrastructure Data Security Relational Databases Database Queries DevOps Digital Architecture Distributed Computing Environment Python (Programming Language) PostgreSQL OpenShift Operational Databases Query Optimization Raw Data Prometheus SQL Databases Data Streaming Workflow Management Systems Data Logging Feature Engineering Snowflake Grafana Apache Spark Change Data Capture Containerization Pyspark Kubernetes Infrastructure Automation Frameworks AWS Data Analytics Apache Kafka Bitbucket Machine Learning Operations Data Pipelines Dynatrace Atlassian Bamboo Docker Elk Stack

Job description

  • As a Data Platform Engineer/Platform Lead within Digital Products, you’ll help build and run the data platform behind our fleet and telematics products - from ingesting raw data through to the datasets and views that power our customer-facing applications. You’ll work closely with Data Science and product teams, balancing hands-on pipeline development with platform-level decisions on cost, reliability, and scale.

  • Responsibilities :

  • Design, build, and maintain data pipelines and orchestration workflows that move data from ingestion through transformation to serving layers

  • Write and optimize SQL and PySpark for large-scale data processing and transformation

  • Tune cloud data warehouse performance and cost (query optimization, refresh/scheduling strategy, resource sizing) as data volume and usage scale

  • Build and maintain data quality checks and pipeline monitoring/alerting to catch issues before they reach downstream consumers

  • Partner with Data Science to support feature engineering and analytics pipelines feeding ML/analytics workloads

  • Collaborate with product and engineering stakeholders to translate business needs into reliable, scalable pipeline design

  • Support incident response, root-cause analysis, and continuous improvement of the data platform

  • Document architecture and pipeline design to support onboarding of new team members

  • Contribute to platform-level decisions on architecture, tooling, and technical direction as the team and data volume scale

Requirements

  • Strong SQL skills, including query optimization

  • Proficient in Python and PySpark for large-scale/distributed data processing

  • Hands-on experience with a workflow orchestration tool (e.g., Apache Airflow)

  • Experience with a cloud data warehouse (e.g., Snowflake)

  • Experience with relational databases (e.g., PostgreSQL)

  • Experience with cloud data infrastructure (AWS), including cloud storage and distributed processing (e.g., S3, EMR/Spark)

  • 8+ years in data engineering with hands-on ownership of production data pipelines

  • Strong communication skills; able to explain technical tradeoffs to both technical and non-technical stakeholders

  • Good to Have

  • Familiarity with streaming or change-data-capture (CDC) ingestion patterns (e.g., Apache Kafka)

  • Experience building data quality frameworks and pipeline observability/alerting

  • Exposure to ML/analytics pipeline support (feature engineering, model-serving data prep)

  • Familiarity with monitoring and logging tools, such as Dynatrace, Prometheus, Grafana, or the ELK stack

  • Strong knowledge of DevOps principles, continuous integration, continuous delivery, and infrastructure automation

  • Hands-on experience with containerization technologies like Docker and container orchestration platforms like Kubernetes or OpenShift

  • Experience with CI/CD and collaboration tooling such as Bamboo, Bitbucket, and Confluence

  • Relevant certifications (e.g., SnowPro Core, SnowPro Advanced: Data Engineer, AWS Data Analytics)

  • Experience building or supporting SaaS products

  • Specialized experience with secure data sharing in Snowflake

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Apply on www.dice.com
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