The Senior Data Engineer will design, build, and optimize data platforms, ensuring best practices in governance, leading project execution, and mentoring junior engineers.
Insomniac Design is a global digital agency headquartered in Washington D.C., with offices in London, Bucharest and Chisinau. We’re an agile, determined and innovative team organized by functional areas of expertise — Creative, Technology, Strategy, and Management. We specialize in human-centered design with deep focus on design thinking and digital transformation.
At Insomniac, we leverage AI to free our teams from routine tasks so they can focus on the aspects of our functions that are most valuable. We thrive on creative problem-solving, collaboration, and innovation. By thoughtfully integrating AI into our workflows, we’re not only improving productivity but also ensuring our people have the tools to do their best work. This empowers us to build smarter solutions and deliver stronger results for our clients.
As a Senior Data Engineer, you will architect, build, and optimize scalable data platforms that empower our clients with unified, actionable insights. You will lead the design of robust data pipelines, enforce best practices in data governance and security, and mentor junior engineers. Your expertise will bridge technical execution and strategic vision, ensuring high-performance, secure, and scalable data solutions that drive business impact.
Technical Leadership & Strategy:
- 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).
- Stay updated with emerging trends, evaluating and integrating new technologies.
Data Architecture & Infrastructure:
- Design and implement scalable data architecture that ensures high availability, security, and performance.
- Define best practices for data modeling, storage, retrieval, and governance.
- Optimize database structures, schemas, indexing, and partitioning for efficient query performance.
- Implement CI/CD for data pipelines and automate infrastructure using Infrastructure-as-Code (IaC) tools.
Data Pipelines & ETL Development:
- Architect and develop end-to-end ETL/ELT pipelines for structured and unstructured data ingestion, processing, and transformation.
- Automate and optimize data workflows using tools like Apache Spark, Kafka, Airflow, and dbt.
- Monitor, troubleshoot, and optimize data pipeline performance.
Data Governance, Security & Compliance:
- Implement data governance policies, including metadata management, lineage tracking, and role-based access control (RBAC).
- Ensure compliance with data privacy regulations (e.g., GDPR, CCPA) and enforce security best practices.
- Develop frameworks for data quality validation, anomaly detection, and integrity checks.
Business & Stakeholder Engagement:
- Collaborate with stakeholders (clients, PMs) to translate business needs into technical specifications and scalable architectures.
- Develop interactive dashboards and reporting solutions to provide actionable insights.
Innovation & Mentorship:
- Lead technical discussions, workshops, and knowledge-sharing sessions within the team.
- Mentor junior engineers, conduct code reviews, and set best practices.
- Drive automation of data workflows, including CI/CD for pipelines and Infrastructure-as-Code (IaC) solutions.
Technical Skills & Experience:
- 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.
Leadership & Soft Skills:
- Proven track record of leading data projects, including migrations, warehousing, and real-time analytics.
- Ability to lead cross-functional teams and manage client expectations.
- Strong problem-solving skills for debugging distributed systems and resolving data anomalies.
- Experience with Agile/Scrum methodologies, including tools like Jira, Git.
- Excellent communication and stakeholder management skills.
Nice-to-Have (Bonus Skills):
- Certifications in cloud/data technologies (e.g., AWS Certified Data Analytics, Google Cloud Data Engineer).
- Experience with ML pipelines (e.g., feature stores, model deployment).
- Contributions to open-source data projects.
Insomniac Design offers a competitive salary and benefits package including health and life insurance as well as 401k contribution. Salary range: $115,000 - $150,000.
Applicant Eligibility: Please note, candidates who are eligible to work in the US without visa sponsorship are eligible to apply. We are not accepting applicants from recruiters or staffing agencies
Similar Jobs
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Lead data engineering efforts within Technology Consulting: design data architecture and pipelines, implement AWS/Redshift and ETL solutions, support BI (QlikView/Oracle BI), coach teams, manage client relationships and SLAs, apply systems thinking to optimize outcomes and validate solutions with stakeholders.
Top Skills:
AWSDatastageDb2ETLJavaManaged ServicesOracle BiPythonQlikviewRedshiftSlasSQL ServerWorkload Orchestration And Scheduling
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Lead data engineering engagements to design, build, and maintain ETL/ELT pipelines and cloud data architectures. Manage client accounts and mentor teams, leverage tools like DataStage, AWS/Redshift, DB2/SQL Server, GoldenGate, and BI/visualization platforms to deliver analytics, performance tuning, and scalable reporting solutions.
Top Skills:
AWSBirtCdcDatastageDb2Etl/EltGlueGoldengateJavaPythonQlikviewRedshiftS3SpotfireSQL Server
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Design, build, and maintain scalable Spark-based ETL pipelines and computed tables in a central data lake. Integrate structured and unstructured IoT, sensor, and external data for analytics, model training, and dashboards. Collaborate with Data Science, Analytics, and ML teams to ensure reliable, high-quality customer-facing datasets.
Top Skills:
AirflowAWSAzureDagsterData LakeDatabricksDelta LakeETLGCPGitGitPrefectPysparkPythonRest ApisSparksqlSQL
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
