Horizon Industries - Databricks Data Engineer
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Requirements
• Ability to hold a position of public trust with the US government. • S. in Computer Science or equivalent • Big data tools: Hadoop, Spark, Kafka, etc. • Relational SQL and NoSQL databases and experience working with relational databases • AWS cloud services: EC2, S3, RDS, Glue, Step Functions, Lamda, EMR, DynamoDB, DocumentDB, Redshift, Aurora, Athena • Data Platforms: Databricks • Data streaming systems: Batch,Kafka, Storm, Spark-Streaming, etc. • Languages: Python, R, Scala, Go • Ability to inspect existing data pipelines, discern their purpose and functionality, and re-implement them efficiently in Databricks. • Extensive knowledge of data warehousing concepts and hands-on experience deploying pipelines using Databricks **a must • Data modeling and database design skills and knowledge of version control • Excellent verbal and written communication skills • Experience architecting scalable and fault-tolerant data solutions across Azure, AWS, and Databricks • Databricks Data Engineer Professional certification a plus. • Preference for candidates with Databricks Professional certifications • What specifically does this role require • Education: Bachelor’s degree in a technical field such as software engineering, engineering, computer science, etc. • Education: • Location : Horizon is headquartered in the heart of Tyson’s Corner, VA. Occasional travel may be required. • Location • Why you will love working with us/ Perks • A comprehensive benefits package including healthcare (medical, dental, vision and disability) • a 401k program where you are 100% vested from day one with an employer match after 90 days. • an Educational Assistance program. • a Student Loan Repayment Program • Gym Reimbursement Program. • Dynamics, passionate, multi-disciplinary team of creative minds to work with, and many more.
Responsibilities
• Build end-to-end implementation of multiple ETL/ELT pipelines, demonstrating efficient data transformation and ingest patterns to move raw data from data producers to an enterprise data ecosystem, with a focus on performance and reliability • Assess and understand the ETL jobs, workflows, BI tools, and reports • Address technical inquiries concerning customization, integration, enterprise architecture and general feature / functionality of data products • Experience in crafting database / data warehouse solutions in the cloud (Preferably AWS, Azure, Alternatively GCP) • Key must have skill sets – Python, SQL, Databricks, AWS Data Services • Experience with message queuing, stream processing, and highly scalable ‘big data’ data stores • Experience manipulating, processing, and extracting value from large, disconnected datasets • Experience manipulating structured and unstructured data for analysis • Experience with data modeling tools and processes • Experience aggregating and transforming data from multiple datasets to create data products • Support an Agile software development lifecycle
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