Data Engineer (US)
appsierra groupSeattle (WA)
About the role
We are seeking a Data Engineer to join our team. The role focuses on designing and maintaining scalable data pipelines across multiple US locations. The ideal candidate has 2–7 years of experience with Python, SQL, and cloud data platforms.
Key responsibilities:
Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
Build and optimize data processing solutions using Python, SQL, and Spark.
Develop data solutions using Databricks and Snowflake.
Manage cloud‑based data platforms and services on AWS.Perform data integration, transformation, and quality validation.
Optimize data pipelines for performance, reliability, and scalability.
Collaborate with Data Scientists, Analysts, Software Engineers, and business teams.
Required qualifications2–7 years of professional Data Engineering experience.
Strong proficiency in Python and SQL.Hands‑on experience with Spark, Databricks, Snowflake, and AWS.Strong understanding of data pipelines, ETL/ELT, and data warehousing.
Excellent analytical and problem‑solving skills.
Strong communication and teamwork abilities.
Nice to have:
Experience with data modeling. Familiarity with additional big data tools (e.g., Hadoop, Kafka).Knowledge of CI/CD practices for data pipelines.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
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Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
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