Back to search
Hays Linkedin · Posted 3mo ago

Senior Manager—Data Engineer

Shanghai

Linkedin
Continue to application Add your email once, then Caio opens the original posting.

Indexed description

About the Role

We are looking for a highly skilled Data Engineer to design, build, and optimize our data infrastructure and pipelines. You will work closely with data scientists, analysts, and product/engineering teams to ensure reliable, scalable, and high‑quality data delivery that supports analytics, machine learning, and business decision‑making.


Key Responsibilities

1. Data Pipeline & ETL Development

  • Design, build, and maintain scalable ETL/ELT pipelines for batch and real‑time data processing.
  • Develop data ingestion frameworks from multiple sources (API, DB, message queues, cloud storage).
  • Ensure data quality, validation, and monitoring across the entire pipeline.

2. Data Architecture & Modeling

  • Design and optimize data warehouse / data lake architectures.
  • Build efficient data models to support BI, analytics, and ML workloads.
  • Implement best practices for data partitioning, indexing, and performance tuning.

3. Data Platform Engineering

  • Develop and maintain data platform components (workflow orchestration, metadata management, lineage tracking).
  • Optimize storage and compute costs in cloud environments.
  • Ensure high availability, reliability, and scalability of data systems.

4. Collaboration & Cross‑Functional Support

  • Work closely with data scientists to productionize ML features and datasets.
  • Partner with engineering teams to integrate data solutions into product systems.
  • Support business teams with data accessibility, documentation, and troubleshooting.

5. Governance, Security & Compliance

  • Implement data governance standards, including data cataloging, lineage, and access control.
  • Ensure compliance with data privacy and security policies.
  • Establish monitoring, alerting, and incident response for data pipelines.


Required Qualifications

Technical Skills

  • Strong programming skills in Python / Java / Scala.
  • Hands‑on experience with SQL and performance tuning.
  • Experience with modern data processing frameworks:
  • Spark, Flink, Beam, Kafka, Airflow, Dagster, Prefect
  • Experience with cloud platforms:
  • AWS / GCP / Azure (e.g., S3, Redshift, BigQuery, Snowflake, Databricks).
  • Solid understanding of data warehouse / data lake architectures.
  • Experience with CI/CD, containerization (Docker), and version control (Git).

Soft Skills

  • Strong problem‑solving and analytical thinking.
  • Ability to work cross‑functionally with engineering, product, and data teams.
  • Good communication skills and documentation habits.

Preferred Qualifications (Nice to Have)

  • Experience with machine learning pipelines or feature stores.
  • Knowledge of data governance frameworks (e.g., DataHub, Amundsen, Collibra).
  • Experience with real‑time streaming (Kafka, Pulsar, Kinesis).
  • Familiarity with dbt for data transformation.
  • Experience in industries such as e‑commerce, retail, fintech, AI, manufacturing.

Education & Experience

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related fields.
  • 5–8 years of experience in data engineering or similar roles.

Free. 20 seconds. No password. See every match in this search.

Create a free Caio profile to unlock more results and save your role and location preferences.

Unlock free search
Want help applying to roles like this? Search Caio for free. If CV tailoring and application tracking get heavy, Full Caio Agent adds a human specialist.
View Full Agent