Job Description:We are seeking Engineers to join our On-Premises to AWS S3 Migration Platform team — a high-visibility program that designs, builds, and operates a secure, scalable migration platform to move object storage data from on-premises, S3-compatible object storage to AWS S3.Responsibilities of the Engineer include:Migration Workflow Ownership & Orchestration1. Own the end-to-end migration workflow from on-premises source buckets to AWS S3 destination buckets, covering manifest-based and non-manifest migration paths.2. Build and operate AWS-based orchestration using Step Functions, Lambda, Fargate, AWS Batch, DynamoDB, SQS, and rclone.3. Implement batching, sharding, task sizing, and retry handling based on documented compute-tier thresholds (DC node, Bare Metal, manifest-required).4. Support express-route (like-for-like) vs. exception-route migrations, using data-detectable criteria to auto-classify buckets where possible.Execution & ValidationAutomate pre-flight dry-run validation (credentials, connectivity, readability/writability, size/object-count limits) as a gate before any real transfer.Implement and verify source freeze — apply deny-write policy centrally and confirm enforcement via synthetic write-attempt checks.Operate the rclone-based migration runtime with correct credential handling (Kerberos keytab, IAM role assumption via STS), KMS-encrypted destinations, and manifest generation for large migrations.Build and run post-migration reconciliation checks comparing source and destination — object count/size match, per-object checksum match, drift detection, version completeness, and configuration parity.Track and enforce the point-of-no-return cutover step — owner written acknowledgment, followed by centrally sealing the source against reads and writes.Governance, Observability & ReportingImplement governance for bandwidth allocation, queue management, prioritisation, throttling, and job tracking across concurrent migrations.Design DynamoDB-backed job, task, queue, bandwidth, and summary state tracking.Build CloudWatch dashboards, logs,



metrics, alerts, and health checks; parse migration logs into structured pass/fail evidence.Track migration progress, escalations, and blockers via Jira; measure success on namespaces closed, not petabytes moved. Produce structured reports and dashboards for stakeholders and senior leadership.Process Improvement & AutomationRigor & Follow-Through: Proactively follow up on outstanding freeze/owner sign-offs; escalate delays per SLA with clear professional communication.Automation-First: Continuously convert manual verification steps (dry-run review, log inspection, reconciliation) into automated, repeatable gate checks to increase migration throughput.Cross-Functional Collaboration: Work with Cloud Platform, Storage Engineering, and Networking teams to resolve connectivity and platform issues; adapt quickly to new tooling as the platform matures.Technical Skills:Basic QualificationsEducation: Bachelor's or Master's in Computer Science, Applied Mathematics, Engineering, or a related quantitative field.Experience: 3–5 years of professional experience in infrastructure engineering, cloud migration, or large-scale enterprise data platform delivery.Languages: Strong Python (boto3, JSON processing, exception handling, logging, dataclasses, streaming files, API integration); Unix/Linux Shell Scripting.Methodology: Familiarity with change management processes in regulated financial industries.Core Infrastructure Competencies: Candidates must demonstrate a solid understanding of the following:1. Object Storage & S3-Compatible APIs: Deep understanding of Amazon S3, S3 Intelligent-Tiering, S3-compatible APIs (e.g., Dell ECS or similar platforms),



object metadata, prefix structures, large object transfers, versioning, and lifecycle policies.2. Migration Tooling (rclone): Hands-on experience configuring and operating rclone for high-volume transfers — copy vs. sync behaviour, checksums, checkers, retries, no-traverse behaviour, stats, logs, and bandwidth limiting.3. AWS Serverless & Compute: Hands-on experience with Lambda, Step Functions, SQS, SNS, EventBridge, API Gateway, SSM Parameter Store, Secrets Manager, ECS Fargate, and AWS Batch.4. DynamoDB: Ability to design and operate tables, keys, indexes, scans, updates, batch writes, Decimal handling, and state-management patterns for job/task tracking.5. Networking: Understanding of AWS Direct Connect, Transit Gateway, VPCs, private subnets, S3 Gateway Endpoints, NAT Gateway scoping, and high-throughput network design for migration traffic.6. IAM & Security: Strong knowledge of IAM roles, cross-account access, STS assume-role, Kerberos keytab auth, Secrets Manager, KMS encryption, and least-privilege design.7. Development Environments: Working knowledge of IDEs such as VS Code, IntelliJ IDEA, and PyCharm.8. AI & Automation Tools: Familiarity with AI engines and assistants (e.g., GitHub Copilot, ChatGPT, Gemini, Claude) to accelerate scripting, validation logic, and reporting.Core Competencies:Acts as a trusted team player who collaborates effectively across multiple teams and functions.Communicates with clarity and confidence — concise written updates, structured verbal briefings, and proactive stakeholder management.Works effectively with general teams across time zones and cultures; builds alignment and resolves issues constructively.Delivery-focused with a strong sense of ownership; drives work to closure and meets commitments.Brings high energy and urgency to achieve targets while maintaining quality and professionalism.Shows intellectual curiosity; asks thoughtful questions, surfaces risks early, and seeks feedback to continuously improve.

📌 AWS Data Engineer (México)
🏢 EPIKSO MEXICO
📍 México