ETL Data Engineer - Apache Nifi at Charlotte, NC (Hybrid Onsite) - CG

ETL Data Engineer - Apache Nifi

Location: Charlotte, NC (Fully Onsite)

Duration: 12+ Months

Note: Local or nearby candidates only

Summary:

• We are seeking an experienced ETL Data Engineer to design, build, and maintain scalable data ingestion and transformation pipelines, with a strong focus on Apache NiFi. The ideal candidate will have hands-on experience developing reliable ETL/ELT workflows that integrate data from diverse sources into enterprise data platforms. Experience with AWS-based data services is a plus but not mandatory.

Required Qualifications:

• 4+ years of experience as a Data Engineer or ETL Developer.
• Strong hands-on experience with Apache NiFi, including processors, controller services, templates, and NiFi Registry.
• Solid understanding of ETL/ELT concepts, data integration patterns, and data pipeline design.
• Proficiency in SQL and experience working with relational databases (e.g., Oracle, SQL Server, PostgreSQL).
• Experience working with structured and semi-structured data formats (CSV, JSON, Avro, Parquet).
• Familiarity with Linux environments and basic scripting (Python or Shell preferred).
• Experience with version control systems such as Git.

Responsibilities:

• Design, develop, and maintain ETL/ELT pipelines using Apache NiFi for batch and near-real-time data ingestion.
• Build reusable, modular NiFi flows with proper versioning, parameterization, and robust error handling.
• Integrate data from multiple sources including relational databases, flat files, APIs, message queues, and streaming platforms.
• Implement data transformation, enrichment, validation, and routing logic to ensure high data quality and reliability.
• Monitor, troubleshoot, and optimize ETL workflows for performance, scalability, and fault tolerance.
• Collaborate with data architects, analytics teams, and downstream consumers to align pipelines with data models and business requirements.
• Implement logging, monitoring, and alerting for data pipelines.
• Follow best practices for CI/CD, version control, and secure data handling.

Preferred / Nice-to-Have Skills:

• Experience with AWS data services such as S3, Glue, Lambda, RDS, Redshift, or EMR.
• Exposure to streaming platforms such as Kafka or similar messaging systems.
• Experience with containerization and orchestration tools (Docker, Kubernetes).
• Knowledge of data lake or data warehouse architectures.
• Familiarity with Agile delivery models and DevOps practices.

Education:

• Bachelor s degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent practical experience).