Data Engineer, Analytics Job Description
Data engineer, analytics
provides thought leadership in the areas of advanced data techniques, including data modeling, data governance, data quality, data access, data integration, data analysis, and data solution design and implementation.
Data Engineer, Analytics Duties & Responsibilities
To write an effective data engineer, analytics job description, begin by listing detailed duties, responsibilities and expectations. We have included data engineer, analytics job description templates that you can modify and use.
Sample responsibilities for this position include:
Provide training and consulting for various technical and non-technical internal teams
Produce and document standard and best practices
Oversee junior and mid-level staff
Be responsible for leading the development of innovative, nonstandard approaches for knowledge discovery and parametric trending of structured and unstructured data and analysis to support advanced health management for complex aerospace systems
Explore and examine data multiple sources in order to develop visual reporting needs to analyze trends in the KPIs regular reporting for assigned customer needs
Architect, Design and develop new systems and tools to
Participates in setting strategy and standards through data
Develop, test and maintain high quality -efficient, scalable- big data and analytics logics that reflect the captured business requirements
Understand where relevant sources of data are in TV & Media eco-systems, and what is the minimum sets needed for each application
Define and implement data acquisition, cleaning and pre-processing mechanisms, having the capability to distinguish key vs
Data Engineer, Analytics Qualifications
Qualifications for a job description may include education, certification, and experience.
Licensing or Certifications for Data Engineer, Analytics
List any licenses or certifications required by the position: AWS, ITIL, SSL, ASQ, RDS, SQS, SNS, S3, LEAN, DP
Education for Data Engineer, Analytics
Typically a job would require a certain level of education.
Employers hiring for the data engineer, analytics job most commonly would prefer for their future employee to have a relevant degree such as Bachelor's and Master's Degree in Computer Science, Engineering, Mathematics, Statistics, Science, Information Systems, Technical, Education, Business, Computer Engineering
Skills for Data Engineer, Analytics
Desired skills for data engineer, analytics include:
Java
Python
Data tools
Manipulation
Techniques
Data modeling
Current industry trends and techniques to formulate solutions within the context of assigned projects
Scala
Access and its governance
Build processes
Desired experience for data engineer, analytics includes:
Experience leveraging Elasticsearch for ingest and query design, or related solution such as Kibana
Strong proficiency with SQL – queries AND writing stored procedures (SAP HANA, MySQL, PostgreSQL)
Powerful hands-on SQL based data extraction skills to manipulate data from common relational database systems (Oracle, SQL Server), distributed systems (Amazon Redshift, Teradata), NoSQL databases (Mongo DB) and cloud based services (like Salesforce, Workday)
4+ years of related technical experience required
1+ years experience in designing BI solutions (preferably in the healthcare industry), reporting or MicroStrategy experience, and application presentation layer experience
Ability to implement technical solutions that meet business requirements
Data Engineer, Analytics Examples
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Data Engineer, Analytics Job Description
Job Description Example
Our innovative and growing company is searching for experienced candidates for the position of data engineer, analytics. To join our growing team, please review the list of responsibilities and qualifications.
Responsibilities for data engineer, analytics
- Support operations throughout the life of the project and when the system is in service
- Design robust, scalable ETL processes that extract and integrate data from various sources
- Work on big data solutions inside of an industry- leading tech stack
- Take an active role in contributing to the team as a developer
- Design, code, deploy and maintaining production code
- Proactively monitor the overall ETL system health and take appropriate actions to improve the existing implementation
- Work in a lean, collaborative environment with minimum management overhead and maximum responsibilities
- Explore and gain mastery of multiple systems and expand your skillset over time
- Apply expertise in quantitative analysis, data mining and presentation of data to develop visually compelling and accurate security reports and dashboards to support metrics, historical data trend analysis, and identification of opportunities to drive continuous improvement
- Partner with the various teams within Global Security to solve problems and identify key business metrics, trends and analytical needs
Qualifications for data engineer, analytics
- Development experience with at least one NoSQL database (MongoDB, Cassandra)
- Experience of working with various cloud technologies, including knowledge of EC2, S3, Cloudera Hadoop incl
- Experience creating real-time analysis tools
- Experience customizing off-the-shelf products custom development of tools for data collection, analysis, and reporting
- Understanding of the Digital/eCommerce space and standard tools (Google Analytics, Adobe Analytics)
- 3+ years experience in designing BI solutions, preferably in the healthcare industry
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Data Engineer, Analytics Job Description
Job Description Example
Our growing company is looking for a data engineer, analytics. Thank you in advance for taking a look at the list of responsibilities and qualifications. We look forward to reviewing your resume.
Responsibilities for data engineer, analytics
- Leverage “agile” data analysis with technology fluency in parallel processing/programming, software/programming languages and OLAP technologies (Ab Initio, Oracle, Microsoft SQL Server Analysis Services, SQL, PL/SQL, MySQL, Spark and Hadoop-JAVA MapReduce)
- Customer demos
- Design, implement and operate data systems to meet the needs of the organization by synthesizing organizational requirements and identifying the best method of presenting the data for business decisions
- In partnership with product owners, work with business partners on data anomalies and requests for information
- Ensure the availability of critical data systems via automation and monitoring
- Develop, recommend and implement process and procedure changes to systematically improve data integrity
- Monitor database performance, implement changes and apply patches and versions when required
- Monitor the quality of data and information, report on results, and identify and recommend system application changes required to improve the quality of data in all applications
- Investigates data quality problems, conduct root-cause analysis, correct errors, and develops process improvement plans across all programs
- Integrate data from multiple sources and design, develop, and generate ad hoc and operational reports in support of objectives
Qualifications for data engineer, analytics
- Proven track record of project management across organizational boundaries, manages and coordinates teams and cross-functional groups worldwide
- Experience applying statistical analysis and process control (SPC), with SBL experience a plus
- Knowledge of big data processing and/or developing applications and data sources via Hadoop/MapReduce, Hive, MongoDB, Neo4J/Titan, MapReduce, HBASE/Cassandra, leveraging tools such as Yarn, Pig, Spark
- Experience with manufacturing tracking software systems and knowledge of semiconductor process/manufacturing, especially in a high-volume production environment a plus
- Develop interactive charts/graphs using Highcharts, HighStocks, etc
- Development of systems supporting advances in within airplane communication networks, factory networks and remote monitoring systems
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Data Engineer, Analytics Job Description
Job Description Example
Our company is growing rapidly and is hiring for a data engineer, analytics. If you are looking for an exciting place to work, please take a look at the list of qualifications below.
Responsibilities for data engineer, analytics
- Gather reporting and analysis requirements and translate into reporting structures data models, including aggregate tables, pivoted tables, relational or dimensional (star-schema) marts
- Provide day-to-day support to end users who are interacting with the data
- Identify causes of systematic and random yield loss, drive to root cause, and implement countermeasures using data analysis methods and process knowledge
- Drive understanding of yield issues, support development and implementation of process BKMs
- Drive/support development and implementation of quality requirements, test conditions, and screens
- Design, architect, document, develop, test and maintain systems and processes to collect, transform, store and enable analysis of structured and unstructured data
- Curate data, ensure data quality and integrity
- Define, develop and test analytics based on client’s needs
- Work hand in hand with experts to identify opportunities and develop functional proof of concepts analytics
- Support and lead the solution of complex technical problems
Qualifications for data engineer, analytics
- Good to have exposure to Big Data technologies like Apache Spark, Hadoop and Cluster administration
- Working knowledge of physical / mechanical systems
- Experience / awareness of key technologies and concepts big data and analytics; Internet of Things; Industrial Internet; Cloud Services
- 5+ years experience in dimensional data modeling, designing and implementing scalable ETL design and mappings, database query construction and data warehousing skills
- Proficient in Stata, R, Python or some combination
- Familiar with Redshift, Hadoop, Java
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Data Engineer, Analytics Job Description
Job Description Example
Our growing company is looking to fill the role of data engineer, analytics. To join our growing team, please review the list of responsibilities and qualifications.
Responsibilities for data engineer, analytics
- Participate in the development of corporate research data files, information platforms or data spaces designed for exploring and understanding the data
- Participate in the development of prototypes for business or research data solutions (dimensional models, model builds) so that business users or predictive modelers may visually understand and explore a new feature or functionality before implementation to expose design assumptions and drive ideation
- Demonstrate high degree of analytic agility to meeting fluid and dynamic business needs in this space
- Mentor other team members in a business technical environment
- Manage, structure and wrangle clinical data (structured and unstructured) for analytics consumption
- Work with subject matter experts to evaluate multiple internal and external datasets for applicability and usefulness in achieving analytics objectives
- Assist in the management of the data environment for local datasets
- Employ appropriate visual, machine learning, and statistical methods to prepare data for use in predictive and prescriptive modeling
- Create data driven solutions that provide structure and assist in the decision making process
- Devise new algorithms to solve problems and tools to automate work efforts
Qualifications for data engineer, analytics
- Self-motivated attitude with an ability to carry ideas from inception to completion
- Passion for video games and making products that delight the player is a big plus
- Bachelors in Computer Science, Industrial Engineering, Operations Management, Management Information Systems, or a related field
- 2-5 years of experience in server-side development - hands-on experience in Java, J2EE, SOA/ REST server development for enterprise software and preferably SAAS products
- Hands on experience with web and application server technologies such as J2EE application server, Apache Tomcat, nginx, Jersey server, OSGi and other relevant frameworks
- Prior working experience in SQL & databases
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Data Engineer, Analytics Job Description
Job Description Example
Our growing company is hiring for a data engineer, analytics. We appreciate you taking the time to review the list of qualifications and to apply for the position. If you don’t fill all of the qualifications, you may still be considered depending on your level of experience.
Responsibilities for data engineer, analytics
- Development of visualization dashboard and indicators that identify anomalous activities
- Understand and document business and operational processes and synthesize potential fraud scenarios and risk indicators
- Collaborate with the project team members and operational staff
- Provide technical direction on data & analytics software and integration projects
- Offer hands-on guidance to a team of 5-15 engineers across the full stack (including UI development and data visualization, mobile app development, data collection and analysis, roundtrip data processing, and platform development)
- Develop and document healthy team process, practices, doctrine in all aspects of IT projects
- Work with scrum master, delivery manager, architects, product team and others within the broader organization to identify opportunities and risks in ongoing projects
- Assign and monitor development tasks across the development team
- Act as liaison to the organization’s technology leadership layer
- Identify skills/talent among current and prospective team members
Qualifications for data engineer, analytics
- Provide client-facing consultancy
- Working experience in Marketing, Online Campaign management, In-store analytics, Payment industry it’s preferred
- Candidates with a PhD in machine learning will be favored
- Experience with Java programming and relational databases and SQL (preferably Oracle) is also needed
- Knowledge of some statistics packages including SAS, SPSS, R, Open Revolution, Revo Analytics is needed
- Ability to work with others in a dynamic and collaborative environment, excellent communication and presentation skills, the capacity to develop their own network inside and outside the company and the capability to work in a decentralized and international team