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Data Engineer

3 weeks, 1 day ago
Vietnam
Full-time
Senior
Data Engineer
Software Development
Apache Airflow Apache Spark AWS Databricks dbt Docker EC2 GitHub Actions GitLab CI Kubernetes MongoDB PostgreSQL Python SQL Terraform
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qode

qode

qode is a company that focuses on unlocking global opportunities and unleashing potential through no-code solutions. They provide tools and services to help individuals and businesses develop software without the need for traditional coding skills.

Internet Software & Services
View All Jobs 15

Description

  • Design and build production-grade data pipelines using batch, streaming, incremental, and CDC-based patterns.
  • Build ingestion workflows from operational sources such as MongoDB, PostgreSQL/RDS, APIs, and event streams.
  • Design and operate data migration workflows, including full load, incremental sync, CDC replay, cutover, rollback, and reconciliation.
  • Convert semi-structured or NoSQL data into reliable relational and analytical models.
  • Build and optimize data processing jobs using Python, PySpark, Spark SQL, SQL, and Databricks.
  • Orchestrate workflows using Apache Airflow and manage connectors using Airbyte or similar tools.
  • Maintain data quality, observability, alerting, backfills, and production reliability across pipelines.
  • Work with AWS services such as S3, Lambda, IAM, EC2, RDS, DMS, SQS, and Kinesis.
  • Build modular, testable transformation layers using dbt where appropriate.
  • Document data flows, source-to-target mappings, pipeline behavior, data contracts, and operational runbooks.

Requirements

  • 5+ years of experience in Data Engineering, not only analytics, BI, or reporting.
  • Proven hands-on ownership of production data pipelines, including design, implementation, deployment, monitoring, debugging, and backfill/recovery.
  • Strong experience building ETL/ELT pipelines with full load, incremental load, and CDC-based patterns.
  • Strong understanding of CDC correctness, including idempotency, deduplication, ordering, deletes/tombstones, late-arriving events, replay, and reconciliation.
  • Hands-on experience with OLTP databases, preferably MongoDB and PostgreSQL/RDS.
  • Practical experience with schema design, including relational modeling, constraints, indexing, normalization/denormalization, and source-to-target mapping.
  • Experience migrating or syncing data between operational systems and analytical platforms, including validation, cutover, rollback, and reconciliation.
  • Strong SQL skills, including joins, CTEs, window functions, query optimization, and debugging incorrect results.
  • Strong Python or PySpark experience for data processing, automation, validation, and pipeline development.
  • Hands-on AWS data pipeline experience using services such as S3, Lambda, IAM, RDS, DMS, SQS, Kinesis, Glue, or equivalent.
  • Advanced dbt modeling, metrics layer, semantic layer, or self-service analytics.
  • BI/dashboarding experience.
  • Great Expectations, Soda, or other data quality frameworks.
  • Databricks Unity Catalog or governance/catalog tools.
  • Terraform or Infrastructure as Code.
  • Docker, Kubernetes, or EKS.
  • CI/CD using GitHub Actions, GitLab CI, or similar.
  • Data warehouse modeling for analytics marts.

Benefits

  • Attractive salary range, with room to negotiate for a strong fit.
  • Hybrid/remote-friendly culture with flexible work location.
  • Flexible hours and async teamwork to protect focus time.
  • Work equipment support.
  • Allowance for certification and skill development.
  • Year-end bonus and performance-based rewards.
  • 22 paid leaves from your 5th year, including the option to take a full month off.
  • Career growth with personal coaching sessions.

Interested in this position?

Apply directly on the company website

Apply Now

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