Data Engineer @Anika Systems
Data Analysis
Salary unspecified
Remote Location
πŸ‡ΊπŸ‡Έ USA Only
Job Type full-time
Posted 2d ago

[Hiring] Data Engineer @Anika Systems

2d ago - Anika Systems is hiring a remote Data Engineer. πŸ’Έ Salary: unspecified πŸ“Location: USA

Role Description

Anika Systems is seeking a skilled Data Engineer to design, build, and optimize scalable data pipelines and platforms supporting federal clients. This role will play a critical part in enabling enterprise data strategies, supporting Office of the Chief Data Officer (OCDO) initiatives, and delivering high-quality, trusted data for analytics, reporting, and mission operations. This opportunity is 100% remote.

Key Responsibilities

  • Data Pipeline Development & ETL/ELT
    • Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data across enterprise platforms.
    • Build scalable data ingestion frameworks for structured and semi-structured data, including XBRL filings and financial datasets.
    • Implement data transformation logic to support analytics, reporting, and regulatory use cases.
    • Ensure data pipelines are reliable, performant, and scalable in cloud environments.
    • Leverage AI-assisted development tools to accelerate pipeline development, testing, and optimization.
  • Cloud Data Platforms & Iceberg Architecture
    • Develop and manage data solutions leveraging AWS services (e.g., S3, Airflow, DAGs, Glue, Lambda, Redshift).
    • Implement and optimize Apache Iceberg table formats for large-scale, ACID-compliant data lakes.
    • Support lakehouse architectures that unify data lakes and data warehouses.
    • Optimize data storage and retrieval strategies for performance and cost efficiency.
    • Enable data platforms that support AI/ML workloads and downstream generative AI use cases.
  • CI/CD & DataOps Engineering
    • Design and implement CI/CD pipelines for data pipelines, infrastructure, and analytics code using tools such as GitHub Actions, GitLab CI, Jenkins, or AWS-native services.
    • Automate build, test, and deployment processes for ETL pipelines and data platform components.
    • Implement DataOps best practices, including version control, automated testing, environment promotion, and rollback strategies.
    • Ensure reproducibility, reliability, and governance of data pipeline deployments across environments.
    • Integrate AI-driven testing and monitoring tools to improve pipeline quality and reduce operational risk.
  • Data Optimization & Performance Engineering
    • Design and implement materialized views and other performance optimization techniques to improve query efficiency.
    • Tune data pipelines and queries for performance, scalability, and cost.
    • Implement partitioning, indexing, and caching strategies aligned to workload patterns.
  • XBRL & Financial Data Processing
    • Develop pipelines to ingest, parse, and normalize XBRL (eXtensible Business Reporting Language) data.
    • Support regulatory and financial data use cases requiring high accuracy and traceability.
    • Ensure alignment with data standards and validation rules for financial reporting datasets.
  • Context Engineering & Data Modeling Support
    • Apply context engineering principles to ensure data is enriched with meaningful metadata, lineage, and business context.
    • Collaborate with Data Architects to support data modeling, schema design, and entity relationships.
    • Enable downstream analytics and AI use cases by structuring data for usability, discoverability, and governance.
  • Metadata, Data Catalog, and Governance Integration
    • Integrate pipelines with enterprise data catalogs and metadata management systems.
    • Support automated metadata capture, lineage tracking, and data quality monitoring.
    • Ensure alignment with data governance frameworks and standards established by OCDO organizations, including AI data readiness and traceability.
  • Stakeholder Collaboration & Agile Delivery
    • Collaborate with data architects, analysts, and business stakeholders to understand data needs and deliver solutions.
    • Participate in stakeholder listening campaigns, workshops, and data discovery efforts.
    • Work in Agile teams to iteratively deliver data capabilities and enhancements.
    • Contribute to identifying and implementing AI-driven efficiencies and automation opportunities across the data lifecycle.

Qualifications

  • Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
  • 5+ years of experience in data engineering, ETL development, or data platform engineering.
  • Strong hands-on experience with:
    • ETL/ELT tools and frameworks
    • AWS data services (S3, Glue, Lambda, Redshift, etc.)
    • Apache Iceberg and modern data lake architectures
  • Experience designing and implementing CI/CD pipelines for data platforms and ETL workflows.
  • Demonstrated proficiency using AI tools and AI-assisted development workflows (e.g., LLM copilots, automated code generation, pipeline optimization tools).
  • Experience processing XBRL or complex financial/regulatory datasets.
  • Proficiency in SQL and Python.
  • Experience implementing materialized views and query optimization techniques.
  • Understanding of data modeling concepts and metadata management.
  • Familiarity with data governance, data quality practices, and data readiness for AI/ML use cases.
  • Ability to work in Agile, DevOps-oriented environments.
  • U.S. Citizenship required; ability to obtain and maintain a federal clearance.

Preferred Qualifications

  • Experience supporting federal agencies such as SEC, DHS, Treasury, or Federal Reserve System.
  • Familiarity with data catalog tools (e.g., Collibra, Alation, ServiceNow).
  • Experience with Apache Spark, Kafka, or other distributed data processing frameworks.
  • Experience enabling data pipelines for AI/ML or generative AI applications.
  • Knowledge of data maturity frameworks (e.g., EDM DCAM, TDWI).
  • Exposure to context engineering or semantic data layer design.
  • AWS or data engineering certifications.
  • Experience with infrastructure-as-code (IaC) tools (e.g., Terraform, CloudFormation) in support of CI/CD pipelines.
Before You Apply
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πŸ‡ΊπŸ‡Έ Be aware of the location restriction for this remote position: USA Only
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Data Engineer @Anika Systems
Data Analysis
Salary unspecified
Remote Location
πŸ‡ΊπŸ‡Έ USA Only
Job Type full-time
Posted 2d ago
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πŸ‡ΊπŸ‡Έ Be aware of the location restriction for this remote position: USA Only
β€Ό Beware of scams! When applying for jobs, you should NEVER have to pay anything. Learn more.
Apply for this position
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Sent Follow-Up βœ“
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Interview Completed βœ“
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