Senior Data Engineer

About this role

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.

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