Senior Data Engineer

Insomniac Design

Senior Data Engineer at Insomniac Design leading the architecture and optimization of data platforms. Building robust data pipelines and ensuring high-performance, secure, and scalable data solutions.

Posted 7/6/2026full-timeWashington, DC • District of Columbia, Washington • 🇺🇸 United StatesSenior💰 $115,000 - $150,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in architecting and implementing enterprise-grade data platforms, including data lakes and warehouses, while ensuring data security, governance, and compliance. Proficient in building scalable ETL/ELT pipelines and optimizing database performance across cloud platforms.

Highest-signal resume keywords

Data EngineeringSQL ExpertisePython ProficiencyCloud Platforms (AWS, GCP, Azure)Big Data Tools (Apache Spark, Kafka, Airflow)

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ArchitectureETL/ELT FrameworksData ModelingDatabase Performance OptimizationData Quality Controls

Tools & Technologies

MySQLPostgreSQLOracleAWS (Redshift, Glue, S3)Azure (Synapse, Data Factory)GCP (BigQuery, Dataflow)Apache SparkKafkaAirflowSnowflake

Industry Keywords

Data GovernanceData SecurityCompliance Frameworks

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSAzureBigQueryCloudETLGoogle Cloud PlatformKafkaMySQLOraclePostgresPythonSparkSQL

About the role

Key responsibilities & impact

Architect and implement enterprise-grade data platforms, including data lakes, warehouses, and real-time pipelines.
Define and enforce data engineering standards, including ETL/ELT frameworks, data modeling, and quality controls.
Lead performance optimization of databases, queries, and pipelines (e.g., partitioning, indexing, cost-efficient cloud solutions).
Design and implement scalable data architecture that ensures high availability, security, and performance.
Define best practices for data modeling, storage, retrieval, and governance.
Architect and develop end-to-end ETL/ELT pipelines for structured and unstructured data ingestion, processing, and transformation.

Requirements

What you’ll need

7+ years of experience in data engineering with a proven track record of building scalable data solutions.
Expertise in SQL and relational database management systems (MySQL, PostgreSQL, Oracle).
Proficiency in Python (or similar languages) for data processing and automation.
Deep understanding of cloud platforms (AWS, GCP, Azure) and cloud-native data services:AWS (Redshift, Glue, S3)Azure (Synapse, Data Factory)GCP (BigQuery, Dataflow)
Hands-on experience with big data tools:Apache Spark, Kafka, Airflow, dbt, Snowflake, Databricks
Expertise in data modeling.
Strong knowledge of data security, governance, and compliance frameworks.

Benefits

Comp & perks

health and life insurance
401k contribution