Sr. Big Data Engineer

Tecla; Teletrabalho; BRL 80.000 - 120.000; Tempo integral

Resumo da oferta

A leading retail technology firm is seeking a Senior Big Data Engineer to enhance customer data accuracy and accessibility. The role demands over 5 years in data engineering with expertise in Python, Airflow, and Spark, among others. This fully remote position offers a structured schedule for work-life balance, two weeks of vacation yearly, and inclusive paid local holidays. The contract is for three months with a possibility of extension, emphasizing a dedicated team integration.

Serviços

Fully remote position

Two weeks of paid vacation

10 paid days for local holidays

Qualificações

• 5+ years of professional experience as a Data Engineer or in a closely related role.
• Strong experience with Python and Apache Airflow.
• Experience with Spark, Spark SQL, and Spark Streaming.

Responsabilidades

• Join the Customer Identity team focused on ensuring accurate customer data.
• Develop high-performance batch and real-time services.
• Empower customer-facing teams to deliver personalized experiences.

Conhecimentos

Data Engineering experience

Python

Apache Airflow

Scala

Apache Spark

Spark SQL

Spark Streaming

SQL

Apache Kafka

GCP

RESTful APIs

Ferramentas

Apache Spark

GCP BigQuery

GCP BigTable

GCP Dataproc

Descrição da oferta de emprego

Monthly salary : $4,000 - $5,000 USD

Native / Bilingual English is required for this role (read / written / spoken). Please upload your CV Resume in English.

Overview

Along with our partner, we are seeking a Senior Big Data Engineer to join the Customer Identity (CI) team that is central to the enterprise, focused on ensuring customer data is accurate, consistent, and readily accessible. This critical data is the foundation for essential business processes, including personalized marketing, analytical reporting, and seamless online and in-store checkout and customer service experiences.

They manage a wide array of high-performance, scalable batch and real-time services. These services are utilized at numerous customer interactions, such as in-store purchases, online orders, rewards program enrollments, and activations from various marketing channels (Email, Direct Mail, SMS, Push notifications, etc.). By leveraging modern development practices, tools, and technology platforms, the CI team builds capabilities that empower customer-facing and checkout teams to deliver personalized, relevant, and frictionless experiences, ensuring customers realize value with every interaction.

Core hours

This team operates in every major US time zone from Pacific to Eastern. Core hours would be considered 10 am CST - 4 pm CST with 2 hours spilling over either direction based on location.

Required Skills (Non-Negotiable)

• 5+ years of professional experience as a Data Engineer or in a closely related role.
• Strong experience with Python.
• Hands‑on experience with Airflow.
• Experience working with Scala.
• Experience with Spark, Spark SQL, and Spark Streaming.
• Experience designing and working with relational and NoSQL databases.
• Direct experience using Apache Kafka.
• Strong ability to write complex SQL queries.
• Experience with GCP, including BigQuery, BigTable, and Dataproc.
• Experience working with RESTful APIs in data pipelines.

Tech Stack

Python, Apache Airflow, Apache Spark, Spark SQL, Spark Streaming, Kafka, Relational Databases, NoSQL Databases, GCP BigQuery, BigTable, Dataproc, RESTful APIs.

Bonus Skills

Experience with Databriks, Snowflake, Java, Springboot.

Duration

3 months; end date being March 31, 2026, with the possibility of being extended based on team needs.

Benefits

A fully remote position with a structured schedule that supports work‑life balance.

The opportunity to join a leading retail innovator transforming the shopping experience through cutting‑edge technology.

Two weeks of paid vacation per year.

10 paid days for local holidays.

• Please note our partner is only looking for full‑time dedicated team members who are eager to fully integrate within their team.