, ETL/ELT processes, and real-time streaming solutions.
Architect, optimize, and monitor
data warehouses, data lakes, and lakehouse environments
.
Collaborate with cross-functional teams to ensure data availability, quality, and performance.
Implement best practices for
data governance, security, lineage, and metadata management
.
Develop and maintain
CI/CD pipelines
for data engineering workloads.
Troubleshoot complex data issues, ensuring high availability and resilience in production.
Mentor junior engineers and contribute to architectural decisions and technical strategy.
Required Skills & Experience
6-10 years
of hands-on experience as a Data Engineer or similar role.
Strong programming experience in
Python
,
Scala
, or
Java
.
Proven expertise with
SQL
and optimizing complex queries.
Extensive experience with
cloud platforms
such as:
AWS
(preferred),
Azure
, or
GCP
Hands-on experience with:
Data warehousing
(e.g., Snowflake, Redshift, BigQuery)
Data lake/lakehouse architectures
Distributed processing frameworks
(e.g., Spark, Databricks, Flink)
Experience building
ETL/ELT pipelines
and working with workflow orchestration tools such as Airflow, dbt, or similar.
Knowledge of
CI/CD
, Git, containerization (Docker), and infrastructure-as-code (Terraform or CloudFormation).
Strong understanding of
data modelling
, data governance, security standards, and best practices.
Experience in Agile development environments.
Job Types: Full-time, Permanent
Pay: 75,000.00-95,000.00 per year
Benefits:
* Work from home
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