Senior Data Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 67d ago
The date the source published, not the day we noticed it (2026-08-27). Last seen at its source 3h ago.
We have tracked this listing since 18 Oct 2026 (15 days). The employer's own board has carried it every time we have read it, most recently 3 hours ago.
Is it remote?
Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
India
No source stated where this role may be worked. This is read from the ad's own words.
What the ad says
…Location: Remote – India Employment…
Pay not stated
Similar roles pay $7,250/mo
Middle 50% of 9 listings that do state pay — Engineering · Senior · India · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
JazzHR employer's own board first seen 15d ago · last seen 3h ago
- location not stated
The listing
Location: Remote – India
Employment Type: Full-Time, Permanent
Job Summary
We are seeking an experienced Senior Data Engineer with 8–10+ years of experience in designing, developing, and managing modern data platforms, data pipelines, and cloud-based analytics solutions. The ideal candidate will have strong expertise in Azure Data Services, large-scale data processing, data warehousing, ETL/ELT frameworks, and cloud-native data architectures. The role requires hands-on experience in building scalable, secure, and high-performance data solutions that support enterprise analytics, reporting, AI, and business intelligence initiatives.
Key Responsibilities
- Design, develop, and maintain scalable data platforms and data pipelines on Microsoft Azure.
- Build and optimize batch and real-time data ingestion frameworks from multiple structured and unstructured data sources.
- Design and implement data lake, data warehouse, and lakehouse architectures to support analytics and reporting workloads.
- Develop and manage ETL/ELT processes using modern cloud-native data engineering practices.
- Implement data transformation, cleansing, validation, and quality frameworks to ensure data accuracy and reliability.
- Collaborate with business stakeholders, data analysts, data scientists, and application teams to understand data requirements and deliver scalable solutions.
- Optimize data storage, processing, and query performance across enterprise data platforms.
- Implement security, governance, monitoring, and compliance best practices across Azure environments.
- Support integration of data platforms with AI/ML, business intelligence, and enterprise applications.
- Participate in architecture reviews, code reviews, troubleshooting, and technical mentoring activities.
- Ensure high availability, scalability, and operational excellence of data platforms and pipelines.
Required Skills & Qualifications
- 8–10+ years of experience in Data Engineering, Data Warehousing, and Enterprise Data Platform development.
- Strong hands-on experience with Microsoft Azure Data Services.
- Expertise in Azure Data Factory (ADF), Azure Synapse Analytics, Azure Data Lake Storage (ADLS Gen2), and Azure SQL Database.
- Experience building and managing large-scale ETL/ELT pipelines and data integration solutions.
- Strong proficiency in SQL, query optimization, and database performance tuning.
- Hands-on experience with PySpark, Apache Spark, and distributed data processing frameworks.
- Strong programming skills in Python, Scala, or Java.
- Experience with dimensional modeling, data warehousing concepts, and modern lakehouse architectures.
- Experience working with structured, semi-structured, and unstructured data.
- Strong understanding of data governance, data quality, metadata management, and security best practices.
- Experience with REST APIs, data integration patterns, and enterprise system connectivity.
- Hands-on experience with Git, CI/CD pipelines, and DevOps practices.
- Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
- Experience with Microsoft Fabric, OneLake, Dataflows, and Fabric Data Engineering workloads.
- Experience with Databricks, Delta Lake, and lakehouse implementations.
- Knowledge of real-time streaming technologies such as Azure Event Hubs, Apache Kafka, or Azure Stream Analytics.
- Experience supporting AI/ML and advanced analytics workloads through enterprise data platforms.
- Familiarity with Power BI datasets, semantic models, and enterprise reporting architectures.
- Experience with data governance tools such as Microsoft Purview.
- Microsoft Azure Data Engineering certifications are highly preferred.
- Experience working in Agile/Scrum environments.
Nice to Have
- Experience with Microsoft Fabric Data Engineering and Analytics solutions.
- Exposure to MLOps and DataOps practices.
- Knowledge of containerization technologies such as Docker and Kubernetes.
- Experience with Infrastructure as Code (Terraform, ARM Templates, or Bicep).
- Familiarity with Snowflake, BigQuery, or other cloud data warehouse platforms.