Senior Data Engineer

This is a remote position.

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.

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.
  

• 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.
  

• 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.