Join our team and be part of the biggest LATAM market expansion!

Deckard Technologies is looking for a Senior Pipeline Engineer/Team Lead to be responsible for ensuring the reliability of Deckard's data pipelines.

We are at a critical part of the Data Engineering organization at Deckard, partnering closely with application engineers, data scientists, and other internal team members to ensure our vast data pipelines, run cost-effectively, accurately and on time.

You have significant experience working with, and balancing the needs and priorities of, a complex set of users. You get excited about having a hands-on development role building a strong data foundation for the company and having a profound impact on Deckard's relationship with data. You are independent and care deeply about people their goals and professional development, as well as the potential impact Deckard, can have helping communities.

• 2 years in an engineering management/team lead role.
• 7+ years python and AWS experience.
• Pyspark, Hive, Presto, Data lake, data catalogue and or data warehouse experience.
• Hands-on experience with AWS services: Glue, Lambda, S3, SNS, Step Functions, CloudWatch, EMR, Batch
• Graphql 
• Advanced English (C1+)

Desirable Experience:

• Web scraping experience.
• React/Typescript.

Responsibilities:

• Own core datasets that power internal and customer-facing products.
• Work closely with analysts, product teams, and data scientists to understand current and future data needs.
• Define and run SLAs for all data sets.
• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet functional/ non-functional business requirements
• Identify, design and implement internal process improvements: automating manual processes, optimising data delivery, re-designing infrastructure for greater scalability.
• Build the infrastructure required for optimal ETL of data from a variety of data sources using SQL, Spark and other AWS 'big data' technologies
• Build and cultivate a thriving team of data engineers and managers, focusing on impact, high trust, reliability, strong cohesion, and retention through the full employee lifecycle.
• Architecting a graphql data mesh system.