Data Engineer

$120k - $140k

Full-time

SFE

Washington DC

Section

Details

Job Title

Data Engineer

Job Type

Full Time

Client Location

Seattle, WA

Work Arrangement

Onsite

Duration

Full Time

Pay Rate / Salary

$120-$140k/yr.

Job Summary

Experienced Data Engineer with strong expertise in designing, developing, and maintaining scalable data pipelines and data processing solutions.
Skilled in data ingestion, transformation, integration, and migration across structured and unstructured data sources.
Proficient in SQL, Python, ETL/ELT processes, cloud data platforms, data warehouses, and distributed data processing technologies.
Experienced in building reliable data pipelines, optimizing data workflows, implementing data quality and governance practices, and collaborating with data scientists, analysts, application teams, and business stakeholders to deliver high-quality, analytics-ready data.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines for ingesting and transforming data from multiple sources.
Develop data integration workflows using Python, SQL, APIs, batch processing, and streaming technologies.
Build and optimize data pipelines for structured, semi-structured, and unstructured datasets.
Develop data models, tables, views, stored procedures, and transformation logic for analytical and operational requirements.
Implement data ingestion from databases, APIs, files, cloud storage, and enterprise applications.
Work with cloud data platforms such as AWS, Azure, or GCP and services including data lakes, data warehouses, and distributed processing frameworks.
Perform data cleansing, validation, deduplication, enrichment, and transformation to improve data accuracy and consistency.
Optimize SQL queries, data pipelines, and processing jobs for performance, scalability, and cost efficiency.
Build and maintain data lake and data warehouse solutions supporting reporting, analytics, and business intelligence.
Implement data quality checks, monitoring, logging, alerting, and error-handling mechanisms across data pipelines.

Required Qualifications

6+ years of data engineering experience
3+ year of experience working in a data engineering, data science, or software engineering capacity
Expertise in writing and maintaining robust data pipelines in SQL and Python
A track record of turning data requirements from stakeholders into actionable plans
Experience with cloud-native solutions
A history of implementing and upholding best practices in data pipelines, ensuring accuracy, consistency, and reliability
5+ years of experience in data warehousing, data modelling, and building/maintaining ETL/ELT pipelines at scale.
Extensive experience with AWS, Google Cloud Platform (GCP), or Azure.
Proficiency in Apache Spark, Kafka, NoSQL databases, and orchestration tools like Apache Airflow.
Strong skills in Python, Java, or Scala.
Deep knowledge of SQL and, specifically, experience with Snowflake, Data bricks, or Redshift.

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Vacancy posted 2 days ago

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