
AWS Data Engineer
6 days ago
About the Role:
We are seeking a highly skilled AWS Data Engineer to design, build, and optimize
large-scale data pipelines and analytics platforms. The ideal candidate will have
strong hands-on expertise in AWS Glue, Athena, Redshift, PySpark, and SQL,
with a solid understanding of data engineering and data warehousing concepts.
You will work on batch and real-time data streaming solutions to enable data-driven
decision-making across the organization.
What You Will Do:
Design and implement streaming data pipelines from IoT sensors, cameras,
vehicle telemetry, and infrastructure systems.
Build scalable infrastructure using AWS Kinesis, Apache Flink, and Spark for
real-time and batch workloads.
Enable time-series feature stores and sliding window processing for mobility
and telemetry patterns.
Integrate simulation outputs and model predictions into AWS data lakes.
Maintain data validation, schema versioning, and high-throughput ingestion
pipelines.
Collaborate with Data Scientists and Simulation Engineers to optimize data
formats (e.g., Parquet, Protobuf, Delta Lake).
Deploy, monitor, and optimize pipelines on AWS cloud and/or edge
infrastructure.
You Are a Strong Candidate If You Have:
3+ years of experience in Data Engineering, preferably with real-time
streaming systems.
Proficiency in Python, SQL, and distributed data systems (Kinesis, Spark,
Flink, etc.).
Strong understanding of event-driven architectures, data lakes, and message
serialization.
Experience with sensor data processing, telemetry ingestion, or mobility data
is a plus.
Familiarity with Docker, CI/CD, Kubernetes, and cloud-native architectures.
Experience building workflows and orchestrating pipelines (e.g., Airflow, Step
Functions, Dagster).
Preferred Qualifications:
Exposure to smart city platforms, V2X ecosystems, or other time-series
paradigms.
Experience integrating data from cameras and IoT sensors into real-time or
batch pipelines.
If this is you connect me at for more details.
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