Posted on Apr 9, 2019 by Public Consulting Group
PCG is seeking a Data Engineer to advise and consult on building, optimizing and maintaining conceptual and logical database models for our clients. For this role, the ideal candidate will be responsible for consulting on the development and optimization of our client s data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support and advise and leas, software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of developing and optimizing an enterprise data warehouse to support our client s next generation data initiatives. Responsibilities PCG currently seeks a Data Architect to work in Olympia, WA. This person will work as part of a technical consulting team with other technical personnel to provide technical services to PCG projects for our clients. This effort may require consultation towards development of user interfaces, business rules, database queries and stored procedures, and enterprise data maintenance. The ideal candidate will interact with internal business and project management teams and various external security partners and deliver data management recommendations based on best practices and established standards for an enterprise data warehouse cloud infrastructure project utilizing AWS and Azure Create and maintain optimal data pipeline architecture, Assemble large, complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. Keep our data separated and secure across national boundaries through multiple data centers and AWS regions. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems
Qualifications A candidate with (2-3) years of experience in a Data Engineer role, who has attained a BS degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: Experience with big data tools: Hadoop, Spark, Kafka, etc. Experience with relational SQL and NoSQL databases, including Postgres and Cassandra. Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc. Experience with AWS cloud services: EC2, EMR, RDS, Redshift Experience with stream-processing systems: Storm, Spark-Streaming, etc. Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc. Experience with architecting data in cloud solutions e.g. AWS, MS Azure and Office365 (SharePoint/OneDrive/Exchange Online) Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Experience building and optimizing big data data pipelines, architectures and data sets. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. Strong analytic skills related to working with unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency and workload management. A successful history of manipulating, processing and extracting value from large disconnected datasets. Working knowledge of message queuing, stream processing, and highly scalable big data data stores. Strong project management and organizational skills. Experience supporting and working with cross-functional teams in a dynamic environment. Team player and relationship builder, able to work with remote peers. Ability to build relationships, engage and influence others, while working with a diverse local and remote team as well as vendors. Ability to work independently in situations with little or no guidance, managing multiple priorities with tight deadlines.
Associated topics: data administrator, data management, data quality, database, database administrator, etl, erp, mongo database, mongo database administrator, sybase
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