The Senior Data Engineer is responsible for designing, building, and maintaining the data pipelines, transformation layers, and data models that power the enterprise lakehouse. This role is a technical anchor on the data engineering team, delivering robust ELT/ETL solutions and serving as a mentor to junior engineers.
KEY RESPONSIBILITIES
▸ Design and implement scalable batch and streaming data pipelines using Apache Spark, Kafka, and Flink
▸ Build and maintain the Bronze/Silver/Gold medallion architecture within the lakehouse (Delta Lake / Iceberg)
▸ Develop and optimize complex SQL and PySpark transformations for large-scale datasets
▸ Integrate structured, semi-structured, and unstructured data sources into the lakehouse
▸ Collaborate with data architects to evolve the physical and logical data models
▸ Implement data quality checks and monitoring using Great Expectations or dbt tests
▸ Write Infrastructure-as-Code for pipeline environments (Terraform, Helm)
▸ Participate in code reviews and enforce engineering standards and best practices
▸ Troubleshoot pipeline failures, performance bottlenecks, and data incidents
▸ Mentor junior and mid-level data engineers and contribute to internal knowledge sharing
REQUIRED QUALIFICATIONS
▸ 6+ years of data engineering experience with a track record of enterprise-scale delivery
▸ Expert proficiency in Python and SQL; PySpark experience required
▸ Hands-on experience with Apache Spark, Delta Lake, or Apache Iceberg
▸ Experience with orchestration tools: Apache Airflow, Prefect, or Dagster
▸ Strong knowledge of cloud data services: AWS Glue, Azure Data Factory, GCP Dataflow
▸ Proficiency with version control (Git), CI/CD pipelines, and containerization (Docker/Kubernetes)
▸ Experience with dbt (data build tool) for transformation layer management
▸ Bachelor's degree in Computer Science, Engineering, or related technical field
PREFERRED QUALIFICATIONS
▸ Experience with Databricks, Snowflake, or Apache Hudi
▸ Knowledge of streaming architectures and Apache Kafka
▸ Certifications: Databricks Certified Data Engineer, AWS Data Analytics Specialty
At Dynata, we deliver the highest quality first-party data to help businesses around the world gain precise insights, activate the right audiences, and confidently measure impact. With industry-leading respondent accuracy, reliability, and a commitment to continuous improvement, Dynata is the trusted foundation for smarter decision-making.
At Dynata, we are committed to creating an inclusive and accessible environment where every employee and customer feels valued, respected, and supported. We strive to build a workforce that reflects the diversity of the communities we serve. Dynata welcomes and encourages applications from individuals with disabilities and is dedicated to fostering a work culture that supports everyone. Accommodations are available upon request for all aspects of the selection process.
Dynata is an Equal Opportunity Employer. We consider all qualified applicants and employees without regard to race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), national origin, marital status, age, disability, genetic information, veteran status, or any other legally protected status under applicable laws.
The base salary range for this position in is $130K-$150K/yr; however, base pay offered may vary depending on location, job-related knowledge, skills, and experience. A discretionary incentive program may be provided as part of the compensation package, in addition to a full range of medical and other benefits, dependent on full-time employment status.
Skills Required
- 6+ years of data engineering experience with enterprise-scale delivery
- Expert proficiency in Python and SQL
- PySpark experience
- Hands-on experience with Apache Spark, Delta Lake, or Apache Iceberg
- Experience with Apache Airflow, Prefect, or Dagster
- Strong knowledge of AWS Glue, Azure Data Factory, or GCP Dataflow
- Proficiency with Git, CI/CD pipelines, and Docker/Kubernetes
- Experience with dbt
- Bachelor's degree in Computer Science, Engineering, or a related technical field
- Experience with Databricks, Snowflake, or Apache Hudi
- Knowledge of streaming architectures and Apache Kafka
- Databricks Certified Data Engineer or AWS Data Analytics Specialty certification
Dynata Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Dynata and has not been reviewed or approved by Dynata.
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Leave & Time Off Breadth — Time off options such as paid holidays, sick time, PTO, and in some cases unlimited PTO are available, with PTO sometimes described as generous. Volunteer time and a “birthday day off” expand the time‑off menu beyond basics.
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Flexible Benefits — Flexible and remote work options are broadly offered across a global and hybrid footprint, including part‑time and work‑from‑home arrangements. This flexibility can make certain entry‑level or side‑income roles feel reasonable for the work involved.
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Wellbeing & Lifestyle Benefits — Perks such as commuter benefits, wellness resources, snacks, gym or cell‑phone reimbursements, and tuition reimbursement are part of the package. Employee resource groups and volunteer opportunities add lifestyle and community support.
Dynata Insights
What We Do
Dynata is the world’s largest first-party data platform for insights, activation and measurement. With a reach that encompasses over 62 million consumers and business professionals globally, and an extensive library of individual profile attributes collected through surveys, Dynata is the cornerstone for precise, trustworthy quality data. The company has built innovative data services and solutions around its robust first-party data offering to bring the voice of the customer to the entire marketing continuum – from strategy, innovation, and branding to advertising, measurement, and optimization. The Dynata data platform, an all-in-one solution for insights, activation and measurement, leverages our robust data, innovative technology and more than 40 years’ experience as a pioneer in consumer and B2B insights. Our vision for the Dynata data platform is to automate the entire marketing continuum, with capabilities to target audiences; uncover insights; connect data; activate, measure and optimize campaigns; and analyze, visualize, publish and share those insights to drive your business growth. We’ve helped more than 6,000 market research firms, brands, media and advertising agencies, publishers, and consulting and investment firms around the world and in every industry accelerate transformation, enable better decision-making, and deliver revenue growth.
