Data Scientist

Wyetech is seeking an experienced Data Scientist to support the development enhancement and maintenance of enterprise data processing capabilities within a mission-critical Intelligence Community cloud computing environment.

The selected candidate will work closely with Government stakeholders and technical teams to identify requirements for new system capabilities extend and maintain bulk data pipelines and enhance multiple applications operating within the customers cloud infrastructure.

The ideal candidate possesses extensive experience with Python Spark PySpark ETL development data modeling SQL databases and large-scale data processing along with the ability to transform complex structured and unstructured datasets into reliable accessible and actionable information.

This position requires strong analytical capabilities hands-on data engineering experience and the ability to collaborate with customers and integration partners in an Agile development environment.

Big Data Processing & Analytics

• Design develop maintain and enhance large-scale data processing capabilities using Python Apache Spark and PySpark.

• Support the development and optimization of bulk data pipelines within enterprise cloud computing environments.

• Process analyze and transform complex datasets to support mission-critical applications and analytical requirements.

• Develop scalable data processing solutions capable of handling structured and unstructured information.

• Perform extensive data reviews and data quality analyses to identify inconsistencies anomalies and processing issues.

• Apply data modeling and transformation techniques to improve data accessibility consistency and usability.

• Support the development of new system capabilities and enhancements to existing cloud-based applications.

• Collaborate with engineering teams to troubleshoot data processing issues and improve pipeline reliability.

ETL Development & Data Integration

• Design develop implement and maintain Extract Transform Load (ETL) processes supporting enterprise data integration.

• Perform data mapping extraction transformation and loading across multiple data sources.

• Integrate disparate structured and unstructured data formats into enriched query-friendly structured datasets.

• Develop indexed data files that support efficient querying reporting and analytical processing.

• Process and transform XML JSON and other supported data formats.

• Develop and maintain source-to-target mappings data dictionaries and ETL design documentation.

• Identify and resolve data integration challenges transformation errors and data quality issues.

• Support ongoing maintenance enhancement and optimization of bulk data pipelines.

• Collaborate with integration partners to ensure accurate data ingestion transformation and delivery.

Database Development & Data Modeling

• Develop and execute SQL queries to retrieve manipulate validate and analyze data.

• Work with relational database technologies including SQL MySQL and PostgreSQL.

• Support data modeling and analytical development using notebooks and integrated development environments.

• Utilize Visual Studio and applicable development tools to support data processing and analytical workflows.

• Develop and maintain structured datasets optimized for analytical queries and reporting.

• Perform data validation reconciliation and quality assurance activities.

• Identify opportunities to improve database queries data structures and processing efficiency.

• Support the integration of relational database information into enterprise data pipelines.

Log Processing Monitoring & Data Visualization

• Process and convert operating system logs and application data logs into actionable reports metrics and dashboards.

• Develop analytical reports and monitoring capabilities using tools such as Amazon CloudWatch and Kibana.

• Analyze log data to identify patterns operational trends anomalies and performance issues.

• Apply Regular Expressions (RegEx) to extract filter and transform relevant information from complex datasets.

• Develop metrics and dashboards that improve visibility into system operations and data processing activities.

• Support reporting solutions that provide actionable insights to technical teams and Government stakeholders.

• Troubleshoot issues involving log ingestion data transformation and reporting accuracy.

• Maintain and enhance reporting capabilities as customer requirements evolve.

Cloud Data Engineering & Application Support

• Support data processing and analytical capabilities within enterprise cloud computing environments.

• Develop and maintain data pipelines supporting multiple cloud-hosted applications.

• Assist with the integration of cloud services into existing data processing workflows.

• Support cloud-based data ingestion transformation storage and analytical reporting.

• Troubleshoot data pipeline failures processing errors and application integration issues.

• Collaborate with cloud engineers and software developers to improve data processing efficiency and system performance.

• Contribute to the implementation of new cloud-based data capabilities.

• Support reliable delivery of analytical data to downstream applications and stakeholders.

Agile Development & Customer Collaboration

• Interface directly with Government customers and integration partners to identify clarify and document technical objectives.

• Translate customer requirements into actionable data processing and analytical development tasks.

• Participate in Agile development activities including task definition scope refinement planning and reviews.

• Collaborate with cross-functional teams to develop and enhance data processing capabilities.

• Provide technical input regarding data integration requirements implementation approaches and development priorities.

• Document analytical methodologies data processing workflows and technical solutions.

• Support testing validation troubleshooting and continuous improvement of data pipelines and applications.

• Communicate technical findings development progress and potential risks to stakeholders.

• Active TS/SCI security clearance with current Full Scope Polygraph (FSP) is required.

• Demonstrated experience using Apache Spark PySpark and Python for large-scale data processing and analytical development.

• Demonstrated experience with data mapping extraction transformation and loading (ETL).

• Experience developing analytical reports using tools such as Amazon CloudWatch and Kibana.

• Experience processing and converting operating system and application data logs into analytical reports metrics and dashboards.

• Experience using Regular Expressions (RegEx) for data extraction filtering and transformation.

• Experience working with SQL MySQL and PostgreSQL.

• Experience processing and transforming data file formats including XML and JSON.

• Experience using integrated development environments and data modeling tools including notebooks and Visual Studio.

• Experience transforming disparate structured and unstructured datasets into enriched query-friendly structured data stored in indexed files.

• Experience performing extensive data reviews data validation and data quality analysis.

• Experience developing ETL design documentation including source-to-target mappings and data dictionaries.

• Experience communicating with customers and integration partners to gather clarify and document technical objectives.

• Experience supporting Agile development activities including task definition scope development and technical reviews.

• Strong analytical troubleshooting and problem-solving skills.

• Excellent written and verbal communication skills.

• Ability to work effectively with cross-functional engineering teams and Government stakeholders.

Advanced Big Data & Analytics

• Experience deploying analytical capabilities using the Databricks Unified Analytics Platform.

• Experience with Amazon Elastic MapReduce (EMR) for executing large-scale data processing workloads.

• Experience joining and processing multiple complex datasets using Apache Spark.

• Experience tuning Spark streaming and batch processing jobs to improve cluster utilization and processing performance.

• Experience developing and deploying complex notebook-based data processing pipelines.

• Experience using Python data analysis libraries including Pandas.

Cloud Services & DevOps

• Experience utilizing cloud services such as:

  • AWS Lambda

  • Amazon Simple Notification Service (SNS)

  • Amazon Simple Queue Service (SQS)

  • Amazon Elastic Compute Cloud (EC2)

• Experience with DevOps and cloud infrastructure tools including:

  • Amazon CloudWatch

  • AWS Lambda

  • Amazon SQS

  • Amazon DynamoDB

  • Amazon Relational Database Service (RDS)

• Experience supporting cloud-based data integration automation and processing workflows.

• Familiarity with scalable cloud architectures and distributed data processing environments.

Elasticsearch & Log Analytics

• Experience working with the Elastic Stack (ELK) including:

  • Elasticsearch

  • Logstash

  • Kibana

• Experience developing log ingestion indexing querying and analytical reporting capabilities.

• Experience integrating Elasticsearch with enterprise data processing and monitoring solutions.

• Experience developing dashboards and visualizations for complex operational datasets.

• Familiarity with performance monitoring log analytics and data-driven operational reporting.

• Develop and enhance data processing solutions supporting large-scale enterprise applications.

• Maintain and optimize bulk data pipelines within cloud computing environments.

• Implement data transformation processes that improve data consistency accessibility and usability.

• Develop reusable analytical workflows and data processing components.

• Support integration of multiple structured and unstructured data sources.

• Analyze data quality issues and implement corrective measures.

• Develop documentation supporting data lineage source-to-target mappings and data dictionaries.

• Support reporting and visualization capabilities for operational and analytical datasets.

• Collaborate with engineering teams to troubleshoot complex data processing and integration challenges.

• Support the development and deployment of new data processing capabilities based on evolving customer requirements.

• Contribute to Agile development activities and continuous improvement initiatives.

Active TS/SCI security clearance with current Full Scope Polygraph (FSP) is required.

Due to federal contract requirements United States Citizenship and position-appropriate security clearance are required.

At Wyetech youll be at the center of an award-winning corporate culture breaking technological barriers and solving real-world problems for our federal government customers. We are committed to hiring the best of the best and in return we offer a world-class truly unique employee experience that is rare within our industry.

Wyetech believes in generously supporting employees as they prepare for retirement. The company automatically contributes 20% of each employees gross compensation to a Simplified Employee Pension (SEP) IRA with no requirement for employee matching. All contributions are fully vested from day one ensuring immediate ownership of retirement funds.

Additional benefits include:

• Wyetech provides a generous PTO plan of up to 200 hours annually aligned with applicable state leave regulations. Employees have the flexibility to adjust their PTO allocation at the start of each calendar year ensuring it meets their evolving needs.

Full-time employees have the option to participate in a variety of voluntary benefit plans including:

• A Choice of Medical Plan Options some with Health Savings Account (HSA)

• Vision and Dental

• Life and AD&D Benefits

• Short and Long-Term Disability

• Hospital Indemnity Accident and Critical Illness Insurances

• Optional Identity Theft and Legal Protection Services

• Employee Referral Bonus Eligibility up to $10000

• Mobility Among Wyetech-supported Contracts

• Various team-building events throughout the year such as monthly lunches summer company picnic and an annual holiday party.

• Employees receive two complimentary branded clothing orders annually.

Hourly pay rates listed for this position serve as a general guideline and are not a guarantee of compensation. Compensation will vary dependent upon factors including but not limited to Government contract rates; education; relevant prior work experience knowledge skills and competencies; certifications; and geographic location. Hourly pay rates reflect the pre-benefit gross wage amounts.

Wyetech LLC is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability or status as a protected veteran.

Affirmative Action Statement:

Wyetech LLC is committed to the principles of affirmative action in all hiring and employment for minorities women individuals with disabilities and protected veterans.

Accommodations:

Wyetech LLC is committed to providing an inclusive and accessible hiring process. If you need any accommodations during the application or interview process please contact Brittney Wood. at 844-WYETECH x727 or We are happy to provide reasonable accommodations to ensure equal access to all candidates.

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