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Data Platform Engineer
Job in
Lancaster, Lancaster County, Pennsylvania, 17622, USA
Listed on 2026-06-06
Listing for:
Compunnel, Inc.
Full Time
position Listed on 2026-06-06
Job specializations:
-
IT/Tech
Data Engineer, Cloud Computing, Data Science Manager, Big Data
Job Description & How to Apply Below
The Data Platform Engineer will be responsible for designing, implementing, and deploying scalable data solutions across diverse technical environments.
The role involves working across streaming, data lakes, analytics, and cloud platforms while ensuring strong performance, security, scalability, and robust data integration.
The position requires hands-on coding skills, collaboration across multiple data technologies, and the ability to create clear technical documentation and presentations.
Key Responsibilities- Design and implement data solutions based on customer needs, covering streaming, data lakes, analytics, and other data platform requirements.
- Recommend appropriate technologies and end-to-end solutions across application, data, and infrastructure layers.
- Develop production-grade data solutions using Python, Java, and Scala with a focus on performance, security, and scalability.
- Collaborate across various technical platforms, including Cloudera, Databricks, Snowflake, and AWS.
- Deliver presentations that explain complex technical concepts clearly and effectively.
- Create detailed solution documentation such as sequence diagrams, logical system views, and class hierarchies.
- Follow Agile methodologies throughout the solution lifecycle.
- Design, build, and deploy databases and data stores to meet organizational and project requirements.
- 4+ years of experience supporting Software Engineering, Data Engineering, or Data Analytics projects.
- 2+ years of experience leading teams on data-related projects and delivering end-to-end technical solutions.
- Ability to travel up to 25%.
- Production experience with core data platforms such as Snowflake, Databricks, AWS, Azure, GCP, or Hadoop.
- Hands-on experience with cloud and distributed storage technologies, including HDFS, S3, ADLS, GCS, Kudu, Elasticsearch/Solr, Cassandra, or other No
SQL systems. - Strong understanding of data integration tools and technologies such as Spark, Kafka, event/streaming frameworks, Stream Sets, NiFi, AWS Data Migration Services, Azure Data Factory, and Google Data Proc.
- Strong written and verbal communication skills for conveying complex technical concepts.
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