Data Engineer — Build Scalable Pipelines & Insights

Amplemarket

United States

À distance

USD 110 000 - 160 000

Plein temps

14 jours+
Générateur de candidature

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Avantages offerts par ce poste

Health Insurance
Stock Options
Annual Company Trip
Nice work environment

Résumé du poste

Amplemarket is seeking a Data Engineer to design, build, and maintain data pipelines and infrastructure for large datasets. You will collaborate with ML, analytics, and product teams to ensure data quality and accessibility for decision-making and product innovation.

Ideal candidates have 3+ years in data engineering, strong Python/SQL, experience with cloud data warehouses (Redshift, BigQuery) and ETL tools (Spark, Databricks, Snowflake), plus excellent communication.

Qualifications

  • 3+ years of experience as a Data Engineer or similar role.
  • Strong programming skills in Python, Java, or a similar language.
  • Experience with SQL and data modeling concepts.

Responsabilités

  • Design and implement data pipelines for collection, storage, and transformation of data from multiple sources.
  • Develop and maintain data models and schema to support analysis and reporting.
  • Write and maintain ETL jobs to load data into the data warehouse.
  • Collaborate with ML engineers, data analysts, and stakeholders to meet data requirements.
  • Monitor and optimize data pipelines to ensure data quality and performance.

Connaissances

Python
SQL
Data modeling
ETL
Cloud data warehousing
Kafka/RabbitMQ

Formation

Bachelor's or Master's in CS/Data Science

Outils

Spark
Flink
Databricks
Snowflake
Redshift/BigQuery

Description du poste

Amplemarket is seeking a Data Engineer to design, build, and maintain data pipelines and infrastructure for large datasets. You will collaborate with ML, analytics, and product teams to ensure data quality and accessibility for decision-making and product innovation.

Ideal candidates have 3+ years in data engineering, strong Python/SQL, experience with cloud data warehouses (Redshift, BigQuery) and ETL tools (Spark, Databricks, Snowflake), plus excellent communication.

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