Company Overview:
At
TechX, we are pioneers in delivering cutting-edge solutions that empower businesses to thrive in today's digital landscape. With a strong focus on
Cloud Transformation (AWS),
Data Modernization, and
Generative AI, we bring unparalleled expertise to drive innovation, efficiency, and growth for our clients.
We specialize in
banking and financial services, retail, manufacturing, and transportation, delivering impactful solutions that address industry-specific challenges and significant market shifts.
Together, we'll build a future where innovation knows no limits.
Job Overview:
We are looking for
1 Junior Data Engineer based in HCMC, focuses on implementing and operating pipelines, tests and monitoring under guidance for Synaptix - TechX's AIOps platform that delivers operational intelligence, including anomaly detection, incident correlation and automated root-cause analysis (RCA) to support CloudOps and DevOps workflows.
Synaptix Data Engineers build, operate and continuously improve the data platform that powers Synaptix's AIOps capabilities. You will implement production-grade batch and real time pipelines that turn logs/metrics/events into minute-level features for ML models and product services, ensure data quality and observability, and work closely with Data Science, MLOps, CloudOps and Product.
Key Responsibilities:
- Build, test and operate ETL/ELT jobs (batch and near-realtime) to produce feature layers and curated datasets for Synaptix.
- Ingest and normalize telemetry sources (CloudWatch/ALB/WAF/K8s/network device logs etc.), store raw curated feature layers and maintain schema contracts/Glue catalog or equivalent.
- Implement data quality and validation (schema checks, DQ gates, unit tests), and maintain monitoring dashboards & alerts (freshness, throughput, error rates).
- Deploy data jobs via CI/CD, automate tests, and maintain runbooks/playbooks for incident triage.
- Own small-to-medium feature pipelines end-to-end: implementation, tests, deployment and monitoring.
- Debug and resolve data pipeline incidents; iterate on DQ checks and dashboards.
- Work with senior engineers to implement idempotency, partitioning and recovery strategies.
- Deliver clear unit tests, README, and handover documentation for every pipeline.
- Produce clear documentation (data contracts, runbooks, onboarding docs) and contribute to team governance artifacts (SharePoint/ClickUp/PMO checkpoints)
Key Requirements:
- 2 years experience building production data pipelines (batch + streaming).
- Proficiency in Python (or Scala/Java) and strong SQL (joins, window functions, partition-aware queries).
- Experience with a cloud data stack (AWS: S3, Glue/Athena, Lambda or equivalent).
- Familiarity with streaming concepts/tools (Kafka/MSK, Kinesis, Flink or Spark Streaming).
- Basic knowledge of data quality practices, monitoring (Grafana/CloudWatch) and CI/CD for data jobs.
- Good written communication and ability to work cross-functionally.
Nice to have:
- Experience with feature stores or ML feature engineering tooling (MLflow, model registry).
- Background in AIOps / RCA / observability domain or experience building features for ML models used in operational intelligence.
- Familiarity with containerization (Docker/K8s) and infra automation (Terraform).
- Knowledge of privacy & PII-safe pipelines, hashing/anonymization patterns.
What We Offer:
- Innovative Environment: A dynamic and collaborative work environment where innovation is encouraged.
- Professional Growth: Opportunities for professional growth and development through continuous learning and exposure to cutting-edge technologies.
- Competitive Package: Competitive salary and benefits package
- Impactful Work: The chance to work on cutting-edge projects with industry-leading clients, making a tangible impact on their business success.
Apply now!
Due to the high volume of applicants, only shortlisted candidates will be contacted. We apologize for this inconvenience!
