Role: Talend Developer Work location: NewPort, OH (Hybrid 2-3 days/week from office) Duration: 12 month We are looking for a skilled Data Ingestion Developer to join our data engineering team. The ideal candidate will be responsible for building and maintaining scalable, efficient data ingestion pipelines that enable seamless data flow from various sources into our data platform. You will work closely with data engineers, architects, and business stakeholders to support data-driven initiatives and ensure data quality, performance, and reliability. Key Responsibilities: • Design, develop, and manage data ingestion pipelines from structured and unstructured data sources (APIs, databases, files, streaming platforms, etc.). • Develop ETL/ELT processes to transform and load data into data warehouses or data lakes. • Integrate data from cloud and on-premise sources using tools like Apache NiFi, Kafka, AWS Glue, Azure Data Factory, or similar. • Ensure high performance, availability, and data integrity of the ingestion workflows. • Collaborate with data architects and analysts to understand data requirements and ensure proper data mapping and transformations. • Monitor and troubleshoot data ingestion failures and performance issues. • Implement data quality checks, validation, and error handling mechanisms. Required Skills and Qualifications: • Bachelor's degree in Computer Science, Information Systems, or a related field. • 3–6 years of experience in data ingestion or data engineering roles. • Hands-on experience with ingestion tools like Apache NiFi, Talend, Informatica, StreamSets, or custom ingestion frameworks. • Experience with cloud platforms such as AWS (Glue, Kinesis, Lambda), Azure (ADF, Synapse), or GCP (Dataflow, Pub/Sub). • Strong programming/scripting skills in Python, Java, or Scala. • Proficient in writing SQL for data extraction and transformation. • Experience with data formats like JSON, Parquet, Avro, XML, CSV. • Familiarity with version control systems (e.g., Git) and CI/CD pipelines. Preferred Qualifications: • Experience with real-time data ingestion using Kafka, Spark Streaming, or Flink. • Knowledge of data governance, cataloging, and metadata management. • Familiarity with data lake and data warehouse technologies (e.g., Snowflake, Redshift, BigQuery, Delta Lake). • Exposure to containerization (Docker, Kubernetes) and orchestration tools (Airflow, Prefect).