Senior AWS Data Engineer

Role Overview

We are seeking a highly skilled Senior Data Engineer to architect, develop, and manage robust, scalable data solutions in a cloud-first environment. This role requires deep expertise in the AWS ecosystem, ETL/ELT frameworks, and data warehousing, along with strong leadership and collaboration capabilities. You will work closely with cross-functional teams to deliver high-performance data infrastructure that drives business insights and operational excellence.

Key Responsibilities

Design, architect, and manage scalable, secure, and reliable data platforms leveraging AWS services (e.g., Redshift, S3, Glue, Lambda)

Build and maintain real-time and batch data pipelines for seamless data ingestion and processing

Develop and optimize high-performance data warehouses and data marts

Write and tune complex SQL queries for analytics, reporting, and data transformation

Collaborate with stakeholders across engineering, analytics, and business units to translate requirements into data solutions

Establish best practices for data architecture, governance, security, and quality

Monitor and ensure high availability, performance, and scalability of data platforms

Mentor junior data engineers and promote a culture of learning and innovation

Stay current with the latest trends in data engineering, cloud technologies, and machine learning integrations

Required Experience & Qualifications

Bachelors or Master’s degree in Computer Science, Data Engineering, or related discipline

7–11 years of experience in data engineering or similar roles, with a strong cloud focus

Advanced proficiency in AWS services, especially Redshift, S3, Glue, Lambda, RDS, and Athena

Strong expertise in SQL, with a focus on query optimization and performance tuning

Proven experience designing and implementing ETL/ELT pipelines and scalable data solutions

Excellent problem-solving, analytical, and communication skills

Demonstrated leadership and mentoring capabilities

Technical Skills

Cloud & Big Data

AWS: Redshift, S3, Glue, Lambda, RDS, Athena, Kinesis, EMR

Data Lake architectures and real-time data processing tools (e.g., Kafka, Flink, Spark Streaming)

Monitoring & Logging: CloudWatch

Programming & Scripting

Advanced SQL, Python, Scala

ETL/ELT & Data Integration Tools

AWS Glue, Apache Airflow, Talend, Informatica

Data Modeling

Dimensional Modeling, Star and Snowflake Schemas

Big Data Frameworks

Apache Spark, Hadoop

CI/CD & DevOps

Git, GitHub, Bitbucket, Jenkins, AWS CodePipeline, Terraform

Governance & Compliance

Working knowledge of GDPR, HIPAA, metadata management, and audit logging

Certifications (Preferred)

AWS Certified Data Analytics or AWS Solutions Architect certification

Additional Requirements

Experience supporting production environments (BAU)

Familiarity with change control processes, incident management, and prioritization

Exposure to both new development and ongoing maintenance/support cycles

Ability to engage with stakeholders at all organizational levels, including external vendors and partners