Remote: Sr. ETL Developer (Talend Big Data Platform)

Remote, USA Full-time
Role Overview We are seeking a seasoned Senior ETL Developer with specialized expertise in the Talend Real-Time Big Data Platform (v6.4.x or higher). You will be responsible for designing, developing, and maintaining complex data integration pipelines that bridge legacy systems with modern big data environments. The ideal candidate is not just a "tool user" but an architect who understands how Talend generates code, manages memory, and interacts with Apache Spark and Hadoop clusters. Key Responsibilities Pipeline Development: Design and develop high-volume ETL/ELT jobs using Talend Studio, focusing on Big Data components (tSparkConfiguration, tMap, tHDFSOutput, etc.). Architecture & Optimization: Optimize Talend job performance by analyzing generated Java code and tuning Spark/MapReduce parameters. Data Management: Implement data quality rules, metadata management, and Master Data Management (MDM) workflows within the Talend ecosystem. Advanced SQL: Write and optimize complex SQL queries for relational databases (Oracle, PostgreSQL, Snowflake) and Big Data environments (Hive, Impala). Real-Time Integration: Build and support real-time streaming interfaces using Talend and Apache Kafka. Collaboration: Act as a technical bridge between Data Architects and Business Stakeholders, translating complex requirements into scalable technical designs. Technical Requirements Talend Expertise: 5+ years of experience with Talend Real-Time Big Data. Must be proficient in Talend Administration Center (TAC) for job scheduling, monitoring, and project management. Big Data Ecosystem: Hands-on experience with the Hadoop stack (HDFS, Hive, YARN) and Apache Spark (Spark Streaming and MLlib). Core ETL/SQL: Expert-level understanding of ETL patterns (Slowly Changing Dimensions, Change Data Capture, Error Handling) and advanced SQL (Window functions, CTEs, Query Tuning). Programming: Strong proficiency in Java (as Talend is Java-based) for creating custom routines and components. Data Modeling: Solid understanding of Star/Snowflake schemas and Data Vault modeling. Soft Skills Communication: Ability to explain technical debt and architectural trade-offs to non-technical leadership. Problem Solving: A "forensic" approach to debugging—identifying whether a failure is in the Talend logic, the Java runtime, or the Hadoop cluster. Apply tot his job
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