Back
Senior (12+ years) specialized data role is remote but still attracts moderate competition.
Data engineering skills transfer across industries, though enterprise finance context adds some domain specificity.
Explicit 12+ years requirement plus many mandatory technologies makes shortlisting highly restrictive.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own end-to-end design, development, and deployment of scalable batch and real-time data pipelines using Snowflake, Amazon Redshift, and AWS services.
Lead data engineering initiatives including data ingestion, ELT transformations using dbt, and data quality across enterprise cloud-native platforms.
Drive platform reliability and operational excellence through monitoring, CI/CD practices, mentoring engineers, and collaboration with cross-functional teams.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.
12+ years of experience in Data Engineering, Data Warehousing, and Software Development.
Hands-on expertise with Snowflake, Amazon Redshift, AWS cloud services (S3, Lambda, Glue, ECS, IAM, CloudFormation), and data transformation frameworks like dbt.
Experience with orchestration tools (Apache Airflow), streaming/CDC technologies (Kafka, STRIIM), and observability platforms (Datadog or equivalent).
Experienced in technical leadership within cloud-native data engineering platforms handling enterprise-scale data workflows.
Proficient in building secure, compliant, and highly available data solutions with strong governance, performance optimization, and data modeling expertise.
Skilled at driving innovation with emerging technologies including AI/ML data enablement, and fostering engineering best practices such as CI/CD, monitoring, and mentoring teams.