Data Engineer

FDM Group

$100K — $120K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-12 years of data or software engineering experience in enterprise environments
  • Advanced proficiency in SQL and Python; Scala or Java is a plus
  • Hands-on experience with Informatica ETL and Hadoop components
  • Familiarity with modern cloud platforms like Azure and containerization technologies
  • Knowledge of CI/CD automation pipelines

Responsibilities

  • Lead the modernization of legacy data systems to cloud-native platforms
  • Develop and maintain data integration and transformation pipelines
  • Implement data quality controls and ensure metadata tracking
  • Focus on system resiliency regarding security and performance
  • Enhance system observability and disaster recovery strategies

Benefits

  • Hybrid work model requiring three days in the office per week
  • Opportunity to work on impactful projects within the financial services sector
  • Initial 12-month project with potential for extension
  • Collaboration with diverse teams in a fast-paced environment
  • Engagement in cutting-edge technology and cloud platforms
Full Job Description
Über die Rolle

This position requires the successful candidate to work on a W2 directly with FDM. We cannot accept C2C, 1099 or employment sponsorship (e.g. H1-B) for this position.

FDM is seeking a Data Engineer located in Charlotte to support a project in the Financial Services sector. Involvement in this project is anticipated to last initially 12 months but may be extended.

This role will be hybrid with requirements to be in office 3 days per week.

Das bringst du mit

Data engineering roles requiring Informatica, Python, and Hadoop focus on legacy platform cloud modernization, building high-performance data pipelines, and migrating massive enterprise data stores to modern cloud ecosystems like Azure, Databricks, and Snowflake.

Key Responsibilities
  • Legacy Modernization: Drive the migration and re-architecture of on-premises data warehouses, legacy Informatica ETL workflows, and Hadoop/Big Data systems into cloud-native environments.
  • Pipeline Development: Build, optimize, and maintain data integration, cleaning, transformation, and control processes using Python and advanced SQL.
  • Data Quality & Governance: Establish rigorous data quality controls, metadata tracking, lineage verification, and Authoritative Data Sourcing (ADS) compliance.
  • System Resiliency: Apply non-functional requirements (NFRs) focused on security, high availability, disaster recovery, performance tuning, and system observability.


Required & Desired Qualifications

  • Experience: 5 to 12+ years in data or software engineering, with significant enterprise background in distributed data architectures.
  • Core Languages: Advanced proficiency in SQL and Python (Scala or Java considered strong pluses)
  • Ecosystems: Hands-on background with Informatica ETL, Hadoop ecosystem components (Hive, HBase, Spark, Kafka), and mainstream RDBMS (Oracle).
  • Cloud & DevOps: Familiarity with modern containerization and cloud platforms (Azure, OpenShift, Kubernetes, Docker, and CI/CD automation pipelines)


Das erwartet dich

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