Job Description
Who we are...
Latitude is a growing Service-Disabled Veteran Owned (SDVOSB) Company within the Federal Sector. We have experience in working with various federal clients across multiple different agencies. We believe in adopting and growing a remote work-from-home culture wherever possible to ensure a healthy work-to-life balance. We believe in automating the mundane and investing in our employees helping them grow their careers over time. We strive for innovation and want to develop solutions that we can take pride in and help break through some of the barriers that exist in technology and the government sectors today.
Description...
We are hiring a Data Engineer to build and run the data pipelines behind analytics and machine learning work on Google Cloud Platform for a federal health customer. You will work with data architects, data scientists, ML engineers, and application teams to ingest, transform, and deliver curated datasets in BigQuery. The role sits on a cloud operations and migration team and includes technical leadership on data engineering standards and practices. This position is fully remote in the United States.
\n What you will do...
Build, maintain, and optimize batch and streaming data pipelines on Google Cloud that support analytics and machine learning.
Ingest data from APIs, databases, SaaS systems, streaming feeds, and files, then transform it and deliver curated datasets in BigQuery.
Build data quality rules, schema validation, and automated tests into pipelines, and monitor pipeline health with Cloud Monitoring and Cloud Logging.
Apply governance and security standards, including IAM, encryption, data masking, and auditing, and maintain pipeline infrastructure with Terraform and CI/CD.
Provide technical direction on data engineering standards, lead code reviews, and document datasets, transformations, and operating procedures.
Minimum qualifications...
Bachelor's degree in computer science, software engineering, information systems, data engineering, or a related technical field.
3+ years of hands-on data engineering experience, including building production data pipelines on a cloud platform.
3+ years leading technical teams, including setting technical standards and processes for cloud and on-premises environments and guiding technology decisions.
Hands-on experience with BigQuery, Cloud Storage, Dataflow, Dataproc, and Pub/Sub.
Strong SQL and Python, with experience in distributed data processing and data modeling.
Experience transforming large datasets and delivering ML-ready datasets for model training.
Ability to obtain and maintain a federal background investigation (Public Trust).
Preferred qualifications...
Master's degree in a technical discipline.
Experience supporting federal government programs, especially federal health.
Knowledge of regulated environments: FedRAMP, HIPAA, NIST 800-53, CIS benchmarks.
Experience with Vertex AI or other ML platforms, and with feature store concepts.
Experience with Cloud Composer (Airflow), dbt, Dataplex, and Datastream for change data capture.
Experience with Apache Kafka or other streaming technologies, and with Looker or Looker Studio.
Security certification such as CISSP or CCSP.
\n $142,000 - $158,000 a year
The posted range is base annual salary, placement within the range depends on qualifications, relevant experience, and contract requirements.
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Clearance...
Applicants selected will be subject to a Security Investigation and May need to Meet Requirements for Access to Protected and/or Classified Information
Citizenship...
Applicants need to be a US Citizen to be considered for the position and have physically resided in the United States for a minimum of 3 years due to background investigation requirements.
Employee Benefits...
Medical, Vision, Dental
Paid Vacation & Sick Time
Paid Federal Holidays
401k Retirement Plan with 100% Company Matching
Employer Paid Life Insurance
Continued Education Assistance
Employee Assistance Program (EAP)
Commuter Benefits Program
Health Savings Account (HSA)
Job Tags
Contract work, Work from home