Cloud Data Engineer
DATAECONOMY (company site, opens in a new tab)8–10 yrsGurugramOn-siteDirect career pageEst. 18–28 LPA
Posted 1d ago
Reach people at DATAECONOMY
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at DATAECONOMY you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead data initiatives by translating business requirements into data integration, sourcing, mapping, and pipeline solutions.
- Own or support enterprise data models and deliverables for operational and dimensional reporting; maintain alignment with corporate data standards and definitions.
- Guide teams on enterprise data use, data quality across sources, and data management standards, policies, tools, and environments.
Minimum Requirements
- Work Experience Required: 8–10 years overall, including 4–6 years in data ingestion, ETL, data warehousing, CDC, and event-streaming technologies.
- Strong hands-on AWS experience for data management and governance; experience building ingestion and transformation pipelines into S3 and creating AWS Glue mappings and data catalogues.
- Hands-on experience designing and implementing data pipelines, ETL, and data warehouse solutions; familiarity with Parquet or Iceberg and unstructured data is required to guide adoption.
- B.E., B.Tech, BCA, or MCA.
Ideal Candidate Profile
- A lead-level data practitioner able to take ownership of designs and initiatives while coordinating requirements across business and technical stakeholders.
- Experienced in complex, multi-source enterprise data environments, including assessing data usefulness, reliability, and cleanliness and supporting operational or dimensional data models.
- Able to guide organizational adoption of emerging data formats and explain technical designs and alternatives to business users and senior decision-makers.