Description:
Taco Bell is seeking to add a savvy Data Engineer to join our growing Data and Analytics team. We are looking for a self-driven Data Engineer proficient with SQL & ETL pipelines who is familiar with Cloud technology preferably AWS and has scripting experience. You will work with cross functional partners and third-party vendors to enrich our customer data assets by acquiring, organizing, and aggregating customer data from various sources to construct a full and accurate 360 view of our customer for use in direct/email marketing, targeted media campaigns and analytics. You will build data pipelines to source, analyze and validate data from internal and external customer data sources. This is a great opportunity to work on state-of-the-art data products in a friendly and fun environment.
Day To Day
- Design and develop highly scalable and extensible data pipelines from internal and external sources using cloud technology such as AWS, Airflow, Redshift, Snowflake, EMR, DBT.
- Implement new source of truth datasets, in partnership with analytics and business teams.
- Collaborate with data product managers, data scientists, data analysts, and data engineers to document requirements and data specifications.
- Develop, deploy, and maintain serverless data pipelines using Event Bridge, Kinesis, AWS Lambda, S3, and Glue.
- Focus on performance tuning, optimization and scalability to ensure efficiency.
- Build out a robust big data ingestion framework with automation, self-heal capabilities and ability to handle data drifts.
- Adopt automated and manual test strategies to ensure data product quality
- Learn and understand how Taco Bell products work and help build end-to-end solutions.
- Ensure high operational efficiency and quality of your solutions to meet SLAs.
- Actively participate in code reviews and summarize complex data into usable, digestible datasets.
Is This You?
- Bachelor’s degree in analytics, statistics, engineering, math, economics, computer science, information technology or related discipline
- 2+ years professional experience in cloud technologies
- 2 - 5 years of experience designing and delivering large scale, 24-7, mission-critical data pipelines and features using modern cloud data architectures
- 2+ years of hands-on experience in Strong coding skills with Python/Pyspark/Spark and SQL
- 3+ years of hands-on experience in ETL pipeline such as Informatica, AWS Glue, DBT etc.
- 3+ years of experience working in Redshift, Snowflake or other relevant databases.
- Expert knowledge in writing complex SQL and ETL development with experience processing extremely large datasets using batch and real time streaming.
- Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions
- Experience integrating data using streaming technologies such as Kinesis Firehose, Kafka
- Experience with AWS Ecosystem, especially Lambda, Redshift, Athena, DynamoDB, Airflow and S3
- Experience integrating data from multiple data sources and file types such as JSON, Parquet, Iceberg formats.
- Experience supporting and working with cross-functional teams in a dynamic environment
- Strong quantitative and communication skill
- Experience with CI/CD tools like Gitlab, Terraform
- Good To Have:
- Proficiency with automated testing using tools like pytest
- Experience contributing to full lifecycle deployments with a focus on testing and quality.
- Experience with data quality processes, data quality checks, validations, data quality metrics definition and measurement
- Experience in data quality tools such as Informatica DQ or similar.