Senior Data Engineer

Dynata, LLC (Connecticut); United States; Remote; USD 130,000 - 150,000; Full time

Job summary

Dynata is hiring a Senior Data Engineer to design, build, and maintain data pipelines powering the enterprise lakehouse. You will lead ELT/ETL solutions, mentor junior engineers, and contribute to scalable data architectures.

Responsibilities include designing batch and streaming pipelines with Spark/Kafka/Flink, implementing Bronze/Silver/Gold lakehouse layers, and optimizing PySpark transformations for large-scale datasets. Join a team advancing data quality and governance.

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.

Responsibilities

• Design and implement scalable batch and streaming data pipelines.
• Build and maintain Bronze/Silver/Gold lakehouse architectures.
• Develop and optimize PySpark transformations for large datasets.
• Integrate structured, semi-structured, and unstructured data sources.
• Collaborate with data architects on data models.
• Implement data quality checks and monitoring.
• Write Infrastructure-as-Code for pipelines (Terraform, Helm).
• Mentor junior engineers and participate in code reviews.
• Troubleshoot failures and performance bottlenecks.

Skills

Python

SQL

PySpark

Apache Spark

Kafka

Flink

Airflow

Dagster

dbt

Docker

Kubernetes

Databricks

Snowflake

Education

Bachelor’s degree in Computer Science, Engineering, or related technical field

Tools

Git

CI/CD

Delta Lake

Iceberg

Job description

The Senior Data Engineeris responsible fordesigning, building, andmaintainingthedata pipelines, transformation layers, and data models that power the enterpriselakehouse. 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

• Designand implement scalable batch and streaming data pipelines using Apache Spark, Kafka, and Flink
• Buildandmaintainthe Bronze/Silver/Gold medallion architecture within thelakehouse(Delta Lake / Iceberg)
• Developandoptimizecomplex SQL andPySparktransformations for large-scale datasets
• Integratestructured, semi-structured, and unstructured data sources into thelakehouse
• Collaboratewith data architects to evolve the physical and logical data models
• Implementdata quality checks and monitoring using Great Expectations ordbttests
• WriteInfrastructure-as-Code for pipeline environments (Terraform, Helm)
• Participatein code reviews and enforce engineering standards and best practices
• Troubleshootpipeline failures, performance bottlenecks, and data incidents
• Mentorjunior and mid-level data engineers and contribute to internal knowledge sharing

REQUIRED QUALIFICATIONS

• 6+ years of data engineering experience witha track recordof enterprise-scale delivery
• Expertproficiencyin Python and SQL;PySparkexperiencerequired
• Hands-on experience with Apache Spark, Delta Lake, or Apache Iceberg
• Experiencewith orchestration tools: Apache Airflow, Prefect, orDagster
• Strongknowledge of cloud data services: AWS Glue, Azure Data Factory, GCP Dataflow
• Proficiencywith version control (Git), CI/CD pipelines, and containerization (Docker/Kubernetes)
• Experiencewithdbt(data build tool) for transformation layer management
• Bachelor’sdegree in Computer Science, Engineering, or related technical field

PREFERRED QUALIFICATIONS

• Experiencewith Databricks, Snowflake, or Apache Hudi
• Knowledgeof 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.