Data Engineer (US)

Appsierra Group; Seattle (WA); On-site; USD 110,000 - 170,000; Full time

Job summary

Appsierra Group is seeking a Data Engineer to design and maintain scalable data pipelines across US locations. The role focuses on Python, SQL, and cloud data platforms.

You will build ETL/ELT workflows, optimize data processing with Spark, Databricks, Snowflake, and AWS, and collaborate with Data Scientists, Analysts, and Engineers to deliver reliable data solutions. 2–7 years of related experience is preferred.

Qualifications

• 2–7 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.

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.

Skills

Python

SQL

ETL/ELT

Data Pipelines

Spark

Databricks

Snowflake

AWS

Communication

Teamwork

Tools

Spark

Databricks

Snowflake

AWS

Job description

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 qualifications

• 2–7 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.