Company
Technology
SeniorDataDeveloper,Analytics&Insights
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Developer, Analytics & Insights”
Industry & Context.
Problem-solving skills
What They're Looking For.
Must Have
5+ years data engineering, 5+ years large-scale data processing, Cloud-based environments experience, AWS expertise, Python programming skills, Advanced SQL proficiency, Data modeling experience, Analytical data warehouses experience, Dimensional modeling techniques experience, Airflow experience, ETL/ELT processes understanding, Traditional data engineering frameworks experience, Modern data engineering frameworks experience, Big data technologies familiarity, Semi-structured data formats experience, JSON handling experience, Parquet handling experience, AWS services knowledge, Cloud-based data architecture knowledge
Nice to Have
DBT experience, Spark SQL experience, REST APIs experience, Containerization experience, AI-native data engineering concepts experience, Infrastructure-as-code exposure, Automation tools exposure
How You'll Work.
Team & Collaboration
Cross-functional stakeholders; Data peers
Communication Scope
Communication skills
Full Job Description
## Accountabilities Design, develop, automate, and maintain scalable ELT/ETL data pipelines that process large volumes of structured and unstructured data from multiple sources. Improve and maintain existing data architecture to ensure reliable, efficient, and secure data flow across platforms. Collaborate with data peers, product managers, and cross-functional stakeholders to gather requirements, define solutions, and document technical designs. Implement best practices for data quality, governance, monitoring, validation, and auditing to ensure trustworthy datasets. Optimize pipeline performance and resource efficiency using modern engineering and AI-native approaches, including anomaly detection and schema evolution. Work with big data technologies and frameworks to support large-scale analytical workloads. Contribute to continuous innovation by adopting emerging tools, technologies, and industry best practices in data engineering. Support integration of data pipelines with cloud infrastructure and analytics platforms to enable downstream insights and reporting. Requirements: 5+ years of experience in data engineering or large-scale data processing within cloud-based environments, with strong AWS expertise. Strong programming skills in Python and advanced proficiency in SQL. Experience with data modeling, analytical data warehouses (e.g., Snowflake, Presto, Hive), and dimensional modeling techniques. Hands-on experience with data pipeline orchestration tools such as Airflow. Strong understanding of ETL/ELT processes and experience working with both traditional and modern data engineering frameworks. Familiarity with big data technologies such as Spark and Hadoop. Experience handling semi-structured data formats such as JSON and Parquet. Knowledge of AWS services (e.g., Glue, Lambda, EMR, EKS) and cloud-based data architecture. Exposure to infrastructure-as-code and automation tools such as Terraform, Git, and Jenkins is an asset. Strong communication, collaborati
Applying for this Senior Data Developer, Analytics & Insights role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Lever
- Lever uses a streamlined one-page form — apply in under 5 minutes.
- LinkedIn import works well; review parsed data before submitting.
- The cover letter field is optional but visible to reviewers — use it to differentiate.
- Referral codes from employees can significantly boost visibility of your application.
ANONYMOUS · UNFILTERED
What do employees actually say about this company?
Real rants from real employees. Read before you apply.