Senior DataOps Engineer (AWS & Security Focused)

Mindera; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

Mindera is seeking a Senior DataOps Engineer with hands-on AWS and data platform experience to design, build, automate, and secure scalable cloud data infrastructure.

You will collaborate across CI/CD, orchestration, and security to ensure reliability, cost efficiency, and compliance while driving automation and DevSecOps practices.

The role offers remote work with a global engineering team and opportunities to explore new AWS capabilities and modern data tooling.

Qualifications

• 6+ years of professional experience in DataOps, DevOps, Data Engineering, or Cloud Platform Engineering.
• At least 4 years of hands-on experience with AWS.
• Strong experience with AWS data services (S3, Glue, Athena, Redshift, EMR).
• Hands-on experience with Terraform and Infrastructure as Code.
• CI/CD pipelines with GitHub Actions, GitLab CI, or AWS CodePipeline.
• Proficiency in Python and SQL.
• Experience with Apache Airflow, MWAA, or AWS Step Functions.
• Docker and Kubernetes familiarity.
• Security-focused engineering practices and cloud security controls.

Responsibilities

• Design, deploy, and maintain scalable AWS data infrastructure.
• Implement security best practices across AWS infrastructure and data pipelines.
• Build and maintain infrastructure using Terraform and IaC.
• Develop and manage automated CI/CD pipelines and containerised workloads.
• Build and maintain reliable data workflows with Airflow, MWAA, or Step Functions.
• Research emerging AWS services and drive automation and security improvements.

Skills

Security mindset

Ownership

Analytical thinking

Troubleshooting

Proactive learning

Tools

AWS

Terraform

GitHub Actions

GitLab CI

CodePipeline

Docker

Kubernetes

Python

SQL

Apache Airflow

MWAA

IAM

KMS

VPC

Secrets Manager

Job description

We are looking for a Senior DataOps Engineer with strong hands-on experience in AWS, data platform engineering, infrastructure automation, and cloud security.

In this role, you will design, build, automate, and secure scalable AWS-based data platforms. You will work across cloud infrastructure, data processing, CI/CD, orchestration, and security, ensuring our data ecosystem remains reliable, efficient, and compliant.

We are looking for someone who enjoys solving complex technical challenges, exploring emerging technologies, and continuously improving cloud infrastructure through automation and security-first engineering practices.

Job title: Senior DataOps Engineer (AWS & Security Focused)

Department: Engineering / Data Engineering

Workplace type: Remote

Experience: 6-12 years

Employment type: Full-time

Key Responsibilities

AWS Data Platform Engineering

• Design, deploy, and maintain scalable, highly available AWS data infrastructure.
• Work with AWS services such as S3, Glue, EMR, Athena, Redshift, and Kinesis.
• Optimise infrastructure performance, reliability, and cost efficiency.

Cloud Security & DevSecOps

• Implement security best practices across AWS infrastructure and data pipelines.
• Manage identity and access controls using AWS IAM, applying least-privilege principles.
• Implement encryption, secrets management, network security, and data protection controls using AWS KMS, Secrets Manager, VPC, and related services.
• Leverage AWS GuardDuty, CloudTrail, and monitoring tools to strengthen security visibility, auditing, and compliance.

Infrastructure Automation & CI/CD

• Build and maintain infrastructure using Terraform and Infrastructure as Code (IaC).
• Develop and manage automated CI/CD pipelines using GitHub Actions, GitLab CI, or AWS CodePipeline.
• Containerise applications and manage containerised workloads using Docker and Kubernetes.
• Automate infrastructure provisioning, configuration, deployment, and operational processes.

Data Orchestration & Governance

• Build and maintain reliable data workflows using Apache Airflow, Amazon MWAA, or AWS Step Functions.
• Work with modern data engineering tools such as dbt.
• Implement monitoring, logging, governance, and automated compliance checks across data workflows.
• Identify and resolve infrastructure bottlenecks and data platform reliability issues.

Continuous Improvement & Innovation

• Research and evaluate emerging AWS services, cloud security practices, and open-source tools.
• Develop proof-of-concepts to address complex infrastructure and operational challenges.
• Drive continuous improvements in automation, security, scalability, and operational efficiency.

Required Skills & Qualifications

• 6+ years of professional experience in DataOps, DevOps, Data Engineering, or Cloud Platform Engineering.
• At least 4 years of hands-on experience with AWS.
• Strong experience with AWS data services, including S3, Glue, Athena, Redshift, or EMR.
• Hands-on experience with Terraform and Infrastructure as Code.
• Strong understanding of AWS security, including IAM, KMS, VPC networking, Secrets Manager, and security best practices.
• Experience building and maintaining CI/CD pipelines using GitHub Actions, GitLab CI, or AWS CodePipeline.
• Proficiency in Python and SQL.
• Experience with data orchestration tools such as Apache Airflow, Amazon MWAA, or AWS Step Functions.
• Familiarity with Docker and Kubernetes.
• Experience with logging, monitoring, auditing, and cloud security controls.

Preferred Qualifications

• Experience with AWS EKS, ECS, Lambda, and Kinesis.
• Familiarity with dbt and modern data platform architectures.
• Experience implementing automated security checks and compliance controls.
• Knowledge of relational and NoSQL database security.
• Experience troubleshooting complex cloud infrastructure and data pipeline issues.
• A strong interest in exploring new AWS capabilities and modern DevSecOps practices.

What We Are Looking For

• A security-first mindset with a strong focus on data privacy and risk management.
• A proactive engineer who enjoys learning, experimenting, and solving unfamiliar problems.
• Strong analytical and troubleshooting skills.
• An ownership-driven approach to infrastructure reliability and automation.
• The ability to balance security, scalability, performance, and operational efficiency.