Data Engineer Jobs

IQZ Systems

Location:
India

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

We’re looking for a hands-on Data Engineer with 2–5 years of experience to build reliable data pipelines, optimize data models, and support analytics and product use cases. You’ll work across batch and streaming workloads in the cloud, ensuring data is accurate, timely, and cost-efficient

Job Responsibility:

Build Pipelines: Develop, test, and deploy scalable ETL/ELT pipelines for batch and streaming use cases
Model Data: Design clean, query-optimized data models (star schema, SCD, slowly changing logic as needed)
SQL Excellence: Author performant SQL for transformations, materializations, and reports
Orchestrate Workflows: Implement DAGs/workflows with Airflow/Prefect
maintain SLAs and retries
Data Quality: Add validation checks, schema enforcement, and alerting (e.g., Great Expectations)
Performance & Cost: Tune Spark/warehouse queries, optimize storage formats/partitions, and control costs
Collaboration: Work with Analytics, Data Science, and Product to translate requirements into data models
Ops & Reliability: Monitor pipelines, debug failures, and improve observability and documentation
Security & Compliance: Handle data responsibly (PII), follow RBAC/least privilege, and secrets management

Requirements:

2+ years of experience
Solid Python (pandas, PySpark or data frameworks)
modular, testable code
Strong SQL across analytical databases/warehouses (e.g., Snowflake/BigQuery/Redshift/Azure Synapse)
Experience building production-grade pipelines and transformations
Exposure to at least one cloud (AWS/Azure/GCP/Databricks) for data storage and compute
Hands-on with Spark (PySpark) or equivalent distributed processing
Airflow or Prefect (DAGs, schedules, sensors, retries, SLAs)
Git workflows
basic CI for data jobs
Good understanding of Parquet/ORC/Avro, partitioning, and file layout
Familiarity with Looker/Power BI/Tableau and semantic modeling

Nice to have:

Familiarity with Data Virtualization Tools like Denodo
Kafka/Kinesis/Event Hubs
basics of stream processing (Flink/Spark Structured Streaming)
Experience with dbt for SQL transformations, testing, and documentation
Collibra, Alation, Ataccamma, Great Expectations, Soda, OpenLineage/Marquez
Docker basics
Kubernetes exposure
Terraform/CloudFormation for data infra provisioning

Additional Information:

Job Posted:
December 09, 2025

Employment Type:

Fulltime

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Data Engineer