Lead Data Engineer

Job Title: Lead Data Engineer

Job location: Remote 

Job Duration: Long-Term Contract 

Interview: Virtual 





Responsibilities:

• Develop and maintain optimal data pipeline architecture.
• Assemble large, complex data sets that meet functional and non-functional requirements of various business areas.
• Identify, design, and implement internal process improvements, including automating manual processes, optimizing data delivery, and re-designing infrastructure for greater scalability.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and 'big data' technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into voting registration, execution, and results, operational efficiency, and other key business performance metrics.
• Collaborate with stakeholders, including the Executive, Data, Design, and Support teams, to assist with data-related technical issues and support their data infrastructure needs.
• Keep data separated and secure across Agency boundaries, such as data centers and cloud regions.
• Create data tools for analytics and data scientist team members to assist them in building and optimizing data products needed to support ongoing operations and data-driven decision-making.
• Work with data and analytics professionals to strive for greater functionality in our data systems.

Qualifications:

• Bachelor's Degree in Computer Science or related field of study, with a minimum of 10+ years of data/database background, including 5+ years acting as a Data Engineer.
• 2-3 years of cloud-based data services experience in AWS, such as ECT, Glue, EMR, RDS, and Redshift.
• Real-time data streaming experience with technologies like Storm, Spark-Streaming, Kafka, or similar.
• Advanced working knowledge of SQL and experience working with relational databases, including 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.
• 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.
• 5+ years of experience in a Data Engineer role, with a degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.
• Experience with big data tools such as Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Oracle, MS SQL Server, Postgres, Cassandra, etc.
• Experience with data pipeline and workflow management tools such as Azkaban, Luigi, Airflow, etc.
• Experience with data integration services solutions from vendors such as Informatica, MuleSoft, Talend, TIBCO, etc.
• Experience with cloud-based data services such as AWS (EC2, Glue, EMR, RDS, Redshift, etc.).
• Experience with stream-processing systems such as Storm, Spark-Streaming, Kafka, etc.
• Experience with object-oriented/object function scripting languages such as Python, R, Java, C++, Scala, etc