Senior Data Engineer (Snowflake | Databricks | Kafka | Airflow | dbt)
Trianz
We are seeking a **Senior Data Engineer** to design, build, and scale modern cloud-native data platforms supporting real-time analytics, enterprise reporting, and high-volume streaming workloads. This role requires strong hands-on expertise in **Snowflake, Databricks, Spark, Kafka, Airflow, and dbt**, along with proven experience building reliable pipelines handling **multi-TB datasets and millions/billions of events per day**.
You will partner with engineering, product, analytics, and business teams to deliver scalable pipelines, optimize performance, improve cost efficiency, and implement DataOps best practices across cloud environments (AWS/GCP).
* Design and build scalable batch + streaming data pipelines using **Kafka, Spark Structured Streaming, Databricks, and Snowflake**
* Develop and optimize ELT workflows using **dbt** and orchestration frameworks like **Airflow**
* Build enterprise-grade data models (star schema, dimensional modeling) for analytics and BI workloads
* Optimize Snowflake performance using clustering, workload isolation, materialized views, and query tuning
* Implement automated testing and validation frameworks using **Great Expectations, pytest, and unit testing**
* Implement CI/CD for data pipelines using **GitHub Actions / GitLab / Jenkins**
* Support cloud migrations from legacy systems into AWS/GCP cloud-native architectures
* Build metadata, lineage, and governance frameworks (IAM, encryption, audit logging, catalog tools like Amundsen)
* Improve data reliability through SLA monitoring, observability, schema enforcement, and pipeline alerting
* Partner with analytics teams to enable self-service dashboards in **Tableau, Power BI, Looker**
* Mentor junior engineers and contribute to architecture reviews and platform best practices
* 7+ years of experience as a **Data Engineer / Senior Data Engineer**
* Strong expertise in **SQL, Python, and PySpark**
* Hands-on experience with **Snowflake** and/or **Databricks**
* Strong experience with **Apache Spark (batch + streaming)**
* Proven experience building real-time pipelines using **Kafka** (Confluent is a plus)
* Experience with workflow orchestration using **Airflow**
* Experience with dbt and modern ELT modeling practices
* Strong knowledge of cloud data services in **AWS and/or GCP**
* Strong performance tuning experience (Spark + Snowflake + Redshift/BigQuery)
* Familiarity with CI/CD and Infrastructure-as-Code tools (Terraform is a plus)
* Experience processing **billions of events/day** or multi-terabyte datasets
* Experience with healthcare or regulated environments (**HIPAA, HITECH**)
* Experience with data governance frameworks (**SOC 2, GDPR**)
* Familiarity with Redshift, BigQuery, Delta Lake, EMR, Glue, Kinesis
* Experience implementing observability and monitoring for data pipelines
* Experience building fraud detection or near real-time analytics systems
Snowflake, Databricks, Spark, Kafka, Airflow, dbt, Python, SQL, AWS (S3, Glue, Kinesis, EMR, Lambda), GCP, Terraform, GitHub Actions/GitLab/Jenkins, Great Expectations, Tableau/Power BI/Looker
- ...Job Summary Seeking a Data Engineer with Spark & Streaming skills to... ...pipelines using tools like Spark, Kafka, and cloud services (GCP)... ...of data warehousing (Snowflake, Redshift) and NoSQL databases... ...Tools: Experience with Airflow, Databricks, Docker, Kubernetes. #J-188...DatabricksSenior
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