***This role is for pipeline purposes only; while we don’t have an immediate opening, we frequently launch new positions, and relevant candidates will be contacted once an opportunity becomes available.***

The Senior Data Engineeris responsible for designing, building, andmaintaining the data 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 

▸  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 

▸  Expertproficiency 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 are committed to fostering an inclusive, accessible environment, where all employees and customers feel valued, respected and supported. We are dedicated to building a workforce that reflects the diversity of our customers and communities in which we live and serve. Dynata welcomes and encourages applications from people with disabilities. We are committed to an inclusive work culture for all our employees. Accommodations by request can be made for all aspects of the selection process.

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