Senior Data Engineer
2 weeks ago
Job Summary:
We are seeking an experienced
Data Engineer
with strong expertise in
AWS cloud services
and
Databricks
to design and implement scalable, high-performance data pipelines. The role involves building and optimizing ETL/ELT workflows, managing big data environments, and ensuring seamless data availability for analytics, AI/ML, and business intelligence use cases.
Key Responsibilities:
- Design, develop, and maintain
data pipelines
and workflows using
AWS (S3, Redshift, Glue, EMR, Lambda, Kinesis, Athena)
and
Databricks
. - Build and optimize
ETL/ELT processes
for large-scale structured and unstructured datasets. - Leverage
Databricks
for data engineering, advanced analytics, and machine learning workloads. - Collaborate with data scientists, analysts, and stakeholders to deliver reliable and scalable data solutions.
- Implement
data governance, quality checks, and monitoring frameworks
. - Ensure high availability, scalability, and cost-effectiveness of data solutions.
Required Skills:
- 7+ years of experience in
data engineering
. - Strong hands-on experience with
AWS cloud services
(S3, Redshift, Glue, EMR, Athena, Lambda, Kinesis). - Expertise in
Databricks
(PySpark, Delta Lake, ML pipelines). - Proficiency in
Python
and
SQL
for data transformation and querying. - Strong understanding of
data warehousing, data modeling, and big data frameworks
. - Experience with workflow orchestration tools (Airflow, Step Functions).
Preferred Qualifications:
- Familiarity with
MLOps/ML integration
within Databricks. - Experience with
real-time/streaming data
(Kafka, Spark Streaming). - Knowledge of
infrastructure as code
(Terraform/CloudFormation). - Exposure to data security, compliance, and governance practices.
-
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