PERM - Data Engineer in Houston, TX at DISYS

Date Posted: 7/17/2018

Job Snapshot

Job Description

Data Engineer

Description:The Production Enhancement division encompasses all of our clients Hydraulic Fracturing and Wellbore Stimulation efforts. H The Applied Sciences R&D team is where it all starts. 
As a data engineer on the Applied Sciences R&D team, you will be working with a diverse global team of data scientists, chemists, engineers, and business leaders addressing some of the most challenging problems in Oil and Gas. We are looking for creative, dynamic, passionate, and driven individuals who have the ability to effectively communicate and influence the business through data-driven decisions and investments. This is a high visibility position and the candidate is expected to frequently interact with upper management to formulate and steer digital strategy. 

As a data engineer, you will: 
• Build robust data pipelines and models on cloud technologies 
• Process, cleanse, and verify the integrity of data used for analysis; process unstructured data and optimize for consumption 
• Develop data set processes for data discovery, modeling, mining and archival 
• Extract and process big data at scale using shell scripting, querying, calling rest APIs, etc. 
• Perform complex data analysis with large volumes of data 
• Maintain and monitor cloud performance and provide solutions for effective parallel computing on cloud 
• Collaborate with data scientists, architects, modelers and IT team members to build new analysis tools and metrics 

Required Qualifications: 
• Minimum of a Bachelor’s degree with 3 years of direct experience 
• 3+ years of experience in big data analytics, management, consulting or comparable role 
• Experience writing complex stored procedure and ad-hoc queries with SQL 
• Expert level proficiency with big data technologies such as Hadoop, Spark, Hive/Pig, MapReduce, HDFS 
• Strong knowledge of relational databases such as Oracle, MySQL, Microsoft SQL server, Postgres SQL 
• Experience with NoSQL databases such as HBase, Cassandra, MongoDB, DynamoDB 
• Expertise in developing ETL/Data Pipeline solutions 
• Experience working with large and complex data sets 
• Strong scripting ability in bash and/or Python 
• Experience with Java, Scala, R and/or Python 
• Excellent communication and interpersonal skills required with the ability to present complex and sensitive issues to all levels of senior management 

Desired Qualifications: 
• M.S. or PhD in Computer Science, Applied Mathematics, Engineering or related discipline 
• Experience with data privacy concerns 
• Experience with stream processing (Kafka, Spark Streaming, Akka, Flink, etc.) 
• Ability to build and maintain modern cloud architecture (e.g. Google Cloud, AWS, etc.) 
• Experience with data visualization software applications (e.g. Spotfire, Tableau, etc.) 
• Knowledge of data science practices for effective support to Data Scientists for its data centric needs 

Other Experience: 
• Candidates having qualifications that exceed the minimum job requirements will receive consideration for a higher level role given (1) their experience, (2) additional job requirements, and/or (3) business needs. 
• Depending on education, experience, and skill level, a variety of job opportunities might be available including Data Engineer Principal, Data Engineer Advisor or Data Engineer Sr. Advisor. 

Job Requirements

Digital Intelligence Systems, LLC. is an Equal Opportunity Employer, M/F/D/V. We do not discriminate against any employee or applicant because they inquired about, discussed, or disclosed compensation. Email recruitinghelp @ disys.com to contact us if you are an individual with a disability and require accommodation in the application process.Digital Intelligence Systems, LLC. is an Equal Opportunity Employer, M/F/D/V. We do not discriminate against any employee or applicant because they inquired about, discussed, or disclosed compensation. Email recruitinghelp @ disys.com to contact us if you are an individual with a disability and require accommodation in the application process.