Senior Data Engineer

Company; United States; Remote; USD 90.000 - 150.000; Vollzeit

Zusammenfassung

Slash is seeking a proactive Data Engineer to design and operate high-volume ETL/ELT pipelines in a fully remote setting. You will implement robust data processing using Talend and Apache Spark (PySpark/Scala), while ensuring data governance, quality checks, and scalable architectures across distributed environments.

You will collaborate with Solution Architects and cross-functional teams, contribute to code reviews, and maintain clear technical documentation in English.

Qualifikationen

• 5+ years hands-on data engineering experience building enterprise data pipelines.
• Proficiency in Talend for pipeline development and deployment.
• Strong Spark (PySpark/Scala) experience for high-performance processing.
• Advanced SQL with performance tuning on large datasets.
• Git, CI/CD, and Agile development practices.
• Conversational English for collaboration, standups, and documentation.
• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or equivalent practical experience.

Aufgaben

• Develop, maintain, and optimize robust ETL/ELT pipelines using Talend.
• Implement high-performance data processing pipelines with Spark.
• Partner with Solution Architects on data governance, schema management, and quality checks.
• Diagnose performance issues, memory leaks, and job failures in distributed environments.
• Write SQL and integrate data into downstream engines and lakehouse storage.
• Participate in daily standups, sprint planning, and code reviews, with clear technical docs.

Kenntnisse

Hands-on data pipelines

Distributed systems

Problem solving

Clear English communication

Ausbildung

Bachelor’s degree in CS/SE/IT

Tools

Talend

Apache Spark

Jobbeschreibung

Slash is a venture building consultancy organization with full in-house product & tech staff to handle all client design and development needs. We operate in a crowded industry where everyone is jockeying for position, aiming to push their brand higher. At Slash, we focus on measured growth, ensuring the success of our clients and building relationships that last rather than short term transactional engagements. We aim to deliver the most value based on sound business strategies and product market fit for our clients’ projects.

With nearly 8 years of experience, we have learned and grown much from our humble beginnings. In all that has happened, we have not lost focus on what matters: our people and our clients, which speaks to the core focus on relationships of our business model.

Who You Are

This is a remote position.

About Slash

Slash is a venture building consultancy organization with full in-house product & tech staff to handle all client design and development needs. We operate in a crowded industry where everyone is jockeying for position, aiming to push their brand higher. At Slash, we focus on measured growth, ensuring the success of our clients and building relationships that last rather than short term transactional engagements. We aim to deliver the most value based on sound business strategies and product market fit for our clients’ projects.

With nearly 8 years of experience, we have learned and grown much from our humble beginnings. In all that has happened, we have not lost focus on what matters: our people and our clients, which speaks to the core focus on relationships of our business model.

Who You Are

You are a proactive, hands‑on Data Engineer with a passion for building reliable, high-volume data pipelines. You bring 5+ years of practical experience implementing enterprise ETL workflows and distributed processing systems, with core expertise centered around Talend and Apache Spark.

You enjoy untangling complex source datasets, optimizing sluggish queries, and working side‑by‑side with Solution Architects to turn high-level designs into performant, clean production code. You value software craftsmanship, write clean and maintainable scripts, and thrive in an asynchronous, cross‑functional remote setting.

Our ideal candidate is:

• A Hands‑On Pipeline Builder: seasoned in constructing dependable batch and streaming ETL jobs that withstand large enterprise data volumes.
  

• A Distributed Systems Tinkerer: comfortable tuning Apache Spark jobs, managing partition bottlenecks, and debugging DAG execution issues.
  

• A Proactive Problem Solver: quick to trace pipeline errors, resolve data quality anomalies, and optimize resource usage across big data clusters.
  

• A Reliable Remote Collaborator: clear, responsive, and comfortable discussing technical details in conversational English within a daily Agile cadence.
  

Responsibilities

• Develop, maintain, and optimize robust ETL/ELT pipelines using Talend to ingest and transform diverse structured and semi‑structured datasets.
  

• Implement high‑performance data processing pipelines and transformation jobs using Apache Spark.
  

• Partner with Lead Solution Architects to implement data governance, schema management, and automated data quality checks.
  

• Diagnose and resolve pipeline performance issues, memory leaks, and job failures across distributed big data environments.
  

• Write performant SQL and assist in integrating data into downstream query engines and lakehouse storage layers.
  

• Participate in daily standups, sprint planning, and code reviews, maintaining clear technical documentation for all delivered pipelines.
  

Requirements

Minimum 5+ years of hands‑on data engineering experience building enterprise data pipelines (Middle/Senior level).

Strong, demonstrable proficiency in pipeline development and deployment using Talend.

Solid hands‑on experience developing and optimizing data processing jobs with Apache Spark (PySpark or Scala).

Advanced SQL proficiency, including performance optimization, indexing strategies, and query tuning on large‑scale datasets.

Practical experience with version control (Git), CI/CD pipelines, and Agile development practices.

Conversational English proficiency (capable of clear technical collaboration, standups, and documentation).

Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or equivalent practical experience.