ODI Technologies
How To Apply To apply, send an email to careers@tidewrk.com with the subject line format: Senior Data Engineer - [Primary Tech Stack / Tools] - [Your Full Name] (e.g., Senior Data Engineer - AWS Glue/Python/Snowflake - Jane Doe OR Senior Data Engineer - AWS/Terraform/dbt - John Smith) Your email must contain: Your updated CV/Resume highlighting continuous long-term employment and relevant data engineering project history. A 2-minute introductory video link (via Loom or Drive) introducing yourself, detailing your primary AWS data stack and tooling, and confirming your ability to commit to a long-term role with US time zone overlap. About The Role We are seeking a highly skilled Senior Data Engineer to design, build, and maintain enterprise-grade data pipelines and AWS-based infrastructure. Operating with high technical autonomy, you will take deep ownership of ETL workflows, data lakes, and automated orchestration to ensure reliable, scalable, and secure data processing. This role requires active collaboration with US-based clients and internal engineering, analytics, and product teams, making overlap with US business hours necessary. Key Responsibilities ETL & Data Pipeline Engineering: Design, build, optimize, and maintain high-throughput ETL/ELT pipelines for large-scale batch and real-time data processing. Data Lake Architecture & Governance: Build and manage AWS-based data lakes, enforcing strict data governance, access controls, and schema evolution rules. AWS Cloud Infrastructure & Services: Deep hands-on implementation across AWS Glue, Lake Formation, Athena, Step Functions, S3, Lambda, EC2, SQS, and EventBridge. Pipeline Monitoring & Optimization: Monitor data workflows, conduct deep-dive troubleshooting, resolve bottlenecks, and continuously optimize query execution and storage costs. Cross-Functional Collaboration: Partner with data analytics teams, product managers, and US-based client stakeholders to define data requirements, architecture, and delivery roadmaps. Infrastructure as Code & Cloud Security (Optional): Manage VPC/VPN configurations, security policies, and deploy infrastructure as code using Terraform, AWS CDK, or CloudFormation. Detailed Data Engineering Technical Stack Candidates are expected to demonstrate hands-on production expertise across the following data engineering ecosystem categories: Core AWS Data Services: AWS Glue (Spark/Python jobs), Lake Formation, Amazon Athena, AWS Step Functions, Amazon S3, AWS Lambda, Amazon EC2, Amazon SQS, Amazon EventBridge. Data Warehousing & Query Engines: Amazon Redshift, Snowflake, Trino/Presto, Apache Hive. Languages & Querying: Python (PySpark, Pandas, Polars), Advanced SQL (window functions, query plan optimization, indexing), Bash/Shell scripting. Workflow Orchestration & Scheduling: AWS Step Functions, Apache Airflow, Prefect, Dagster. Infrastructure as Code (IaC) & DevOps: Terraform, AWS CDK, AWS CloudFormation, Git, GitHub Actions, GitLab CI/CD. Networking, Security & Governance: AWS VPC, Site-to-Site VPN, IAM Policies, AWS KMS, Lake Formation fine-grained access control, Data Privacy & OWASP best practices. Data Quality & Testing: Great Expectations, dbt (data build tool), PyTest for data pipelines. Required Qualifications Professional Experience: 4–8+ years of hands-on production experience in data engineering, ETL development, and AWS cloud data infrastructure. Employment Stability (Non-Negotiable): Proven track record of continuous, long-term employment. Candidates with a history of job-hopping, frequent short-term freelancing switches, or unexplained tenure gaps will not be considered. Engagement Setup: Full-time (40 hours/week) Independent Contractor commitment on a dedicated schedule requiring active overlap with US business hours. Workspace Requirements: Quiet home office environment equipped with a functional desktop or laptop computer, reliable high-speed internet, and a working webcam (mobile devices are strictly prohibited). Preferred & Specialized Skills Advanced Network Infrastructure: Direct experience configuring VPC/VPN setups, transit gateways, and private endpoints for secure data transfers. Modern Data Stack: Hands-on experience with dbt, streaming data pipelines (Amazon Kinesis, Apache Kafka), or real-time analytics engines. Client-Facing Execution: Proven experience articulating complex data architecture to non-technical client stakeholders and leadership. Recruitment Guidelines Anti-Fraud Policy: Use of AI-assisted response scripts during evaluations, proxy interviewers, or identity misrepresentation is strictly prohibited and will result in immediate disqualification. Data Privacy: All interview sessions are recorded and processed strictly for internal recruitment evaluation in compliance with applicable data privacy laws. Job Type: Full-time Benefits Flexible schedule Flextime Pay raise Work from home Application Question(s): How many years of professional experience do you have in data engineering, specifically building ETL pipelines and data workflows? Which AWS services have you used in production? (Glue, Lake Formation, Athena, Step Functions, S3, Lambda, EC2, SQS, EventBridge) Are you available to work overlapping hours with US-based clients for collaboration and meetings? Do you have experience with VPC/VPN setup or infrastructure as code tools (Terraform, CDK, CloudFormation)? If yes, please briefly describe. Work Location: Remote
ODI Technologies
