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Key Responsibilities and Required Skills for Upload Engineer

💰 $ - $

EngineeringData EngineeringPlatform

🎯 Role Definition

The Upload Engineer is a technical specialist responsible for designing, building, operating, and improving large-scale file and data ingestion systems that reliably accept, validate, transform, and route files and payloads from partners, customers, and internal systems into company platforms. This role focuses on secure file transfer protocols (SFTP/FTP/FTPS), cloud object storage (S3/GCS/Blob), REST APIs, automated ETL pipelines, monitoring and alerting, throughput and latency optimization, and robust error handling. The ideal candidate blends strong engineering skills (Python, Java, SQL, distributed systems), operational mindset (CI/CD, observability, runbooks), and stakeholder-facing experience (onboarding partners, defining SLAs, data contracts).

📈 Career Progression

Typical Career Path

Entry Point From:

  • Data Engineer (Junior / Mid)
  • DevOps / Site Reliability Engineer
  • Integration or ETL Developer

Advancement To:

  • Senior Upload Engineer / Senior Data Ingestion Engineer
  • Lead Data Engineer or Platform Engineer
  • Engineering Manager / Head of Data Platform
  • Data Platform Architect

Lateral Moves:

  • Data Integration Engineer
  • ETL Developer / Pipeline Engineer
  • API Platform Engineer

Core Responsibilities

Primary Functions

  • Design, implement, and maintain high-throughput, fault-tolerant file ingestion pipelines that accept multiple file formats (CSV, JSON, XML, Avro, Parquet) over SFTP/FTPS/HTTP/HTTPS and streaming protocols, ensuring data integrity and throughput SLAs.
  • Build and operate secure file transfer endpoints and partner onboarding flows, including certificate/key management, IP allowlisting, secure credential exchange, and automated provisioning scripts for new clients.
  • Develop ingestion adapters and connectors (Python/Java/Go) for partner systems, third-party SaaS, and internal producers to reliably push data into object storage (AWS S3, Google Cloud Storage, Azure Blob) and message brokers (Kafka, Kinesis).
  • Implement schema validation, field-level validation rules, and automated data quality checks during ingest (checksum validation, row counts, schema evolution handling) and route invalid payloads to quarantine/exception stores with clear remediation metadata.
  • Create and maintain ETL/ELT orchestration using Airflow, Prefect, or similar schedulers; implement idempotent and resumable jobs, backfill strategies, and time-windowed ingestion patterns.
  • Build and operate APIs and webhooks that accept uploads and streaming events, including request throttling, rate limiting, authentication (OAuth, JWT), and API gateway configuration to protect backend services.
  • Design and implement retry logic, dead-letter queues, exponential backoff, and circuit breakers to handle transient network and downstream service failures while preserving ordering semantics where required.
  • Optimize upload throughput and latency for large file transfer scenarios by implementing multipart uploads, parallelization, chunked streaming, and client-side resumable uploads.
  • Implement end-to-end encryption, data-at-rest encryption, and secure key management for sensitive uploads; ensure compliance-ready logging and access controls for PII and regulated data flows.
  • Integrate ingestion pipelines with CI/CD, infrastructure-as-code (Terraform/CloudFormation), and container platforms (Docker, Kubernetes) to enable repeatable, observable deployments and rollback strategies.
  • Design and implement monitoring, alerting, and observability (Prometheus, Grafana, Datadog, CloudWatch) for ingestion health, throughput, latency, error rates, and SLA adherence; author runbooks for common failure modes.
  • Participate in on-call rotations to investigate and remediate production ingestion incidents; perform postmortems and drive remediation efforts and preventative engineering changes.
  • Collaborate with partner onboarding, account management, and product teams to gather upload requirements, define data contracts and SLAs, write clear integration guides, and deliver partner-facing test harnesses.
  • Maintain metadata catalogs and lineage for ingested datasets, ensuring discoverability and traceability from source file to downstream data products, and support data governance initiatives.
  • Implement cost-optimized storage and lifecycle policies for uploaded content (tiering, compression, deduplication), and advise on retention policies to control storage spend while preserving business access.
  • Automate data validation and reconciliation reports that compare source file attributes to ingested records (row counts, checksums, record-level reconciliation) and notify stakeholders on discrepancies.
  • Perform capacity planning and load testing for ingestion services to ensure scalability during peak on-boarding and seasonal traffic spikes; tune components to prevent backpressure on downstream systems.
  • Build partner-facing developer tooling such as sample clients, SDKs, CLI utilities, and documentation to accelerate integrations and reduce support load.
  • Conduct security reviews and threat modeling for the ingestion surface area, address vulnerabilities in upload handlers and parsers (malicious payloads, zip-bombs, injection), and remediate by design.
  • Define and enforce best practices for file naming, partitioning, compression, and schema evolution to reduce downstream transformation complexity and cost.
  • Collaborate with Data Engineering, BI, and ML teams to ensure uploaded datasets meet downstream quality and format requirements, provide onboarding support, and iterate on ingestion transformations.
  • Maintain and evolve testing frameworks for ingestion logic (unit, integration, and end-to-end tests with sample payloads and partner mocks) to ensure reliability during change.
  • Track and report KPIs for ingestion operations (time-to-first-byte, time-to-complete-upload, ingestion success rate, MTTR), and present data-driven improvements to leadership and stakeholders.
  • Mentor junior engineers on design patterns for reliable uploads, error handling, and production operational excellence; participate in hiring and interviewing for the platform/integration team.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.

Required Skills & Competencies

Hard Skills (Technical)

  • Strong programming skills in Python and/or Java (writing robust, production-grade ingestion/adapter code).
  • Deep experience with cloud storage and object APIs (AWS S3, Google Cloud Storage, Azure Blob) and multipart/resumable uploads.
  • Proficiency with secure file transfer protocols and servers (SFTP, FTPS, FTP, SCP) and managed transfer services.
  • Familiarity with message brokers and streaming platforms (Apache Kafka, Kinesis, Pub/Sub) and integrating file ingestion with streaming pipelines.
  • Solid SQL skills for validation, reconciliation, and downstream transformations; experience with OLAP/warehouse systems (Snowflake, Redshift, BigQuery).
  • Experience with orchestration tools (Apache Airflow, Prefect, Luigi) and building idempotent, schedulable ingestion workflows.
  • Knowledge of CI/CD, containerization (Docker), and Kubernetes for deploying ingestion services at scale.
  • Experience with monitoring and observability tools (Prometheus, Grafana, Datadog, CloudWatch) and alerting strategy design.
  • Competence in designing for security and compliance (encryption in transit/at rest, IAM, audit logging, data privacy controls).
  • Familiarity with schema management and data contract tooling (Avro/Parquet/Protobuf, Confluent Schema Registry).
  • Experience with infrastructure-as-code (Terraform, CloudFormation) for repeatable onboarding and environment provisioning.
  • Ability to implement resilient retry/backoff strategies, dead-letter queues, and graceful degradation patterns.
  • Practical experience with performance tuning for high-volume data transfer and cost optimization strategies.
  • Knowledge of common file parsing libraries, streaming parsers, and protection against malformed payloads and resource exhaustion.
  • Experience with partner integration processes, writing developer documentation, and creating test harnesses or SDKs.

Soft Skills

  • Strong written and verbal communication — capable of documenting contracts, runbooks, and onboarding guides for technical and non-technical stakeholders.
  • Customer and partner-facing mindset — skilled at managing expectations, triaging integration issues, and delivering onboarding success.
  • Problem-solving and analytical thinking — diagnosing complex distributed system failures and identifying permanent fixes.
  • Attention to detail and strong quality orientation for data integrity and reconciliation checks.
  • Collaboration and cross-functional teamwork — working effectively with product managers, security, compliance, and analytics teams.
  • Time management and prioritization — balancing feature work, technical debt, and production support.
  • Mentoring and knowledge-sharing — helping junior engineers grow and maintaining shared team standards.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or equivalent practical experience.

Preferred Education:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Software Engineering, or related STEM field; relevant certifications in cloud platforms or security are a plus.

Relevant Fields of Study:

  • Computer Science / Software Engineering
  • Data Engineering / Data Science
  • Information Systems / Cybersecurity
  • Cloud Computing / DevOps

Experience Requirements

Typical Experience Range:

  • 3–7 years of hands-on engineering experience in file ingestion, data pipelines, systems integration, or related platform engineering roles.

Preferred:

  • 5+ years with demonstrable experience building production-grade ingestion pipelines, partner onboarding for data feeds, and operating file transfer infrastructure in a cloud environment. Experience with regulated data and enterprise integrations is strongly preferred.
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