
Senior Data Engineer
7 days ago
Senior Data Engineer
Location:
Pune
Experience:
4–6 years
Education:
Bachelor's or Master's degree in Computer Science, Information Technology, or a related field
Job Description
Byond is hiring for a
confidential client
in the manufacturing domain. We are seeking a highly skilled
Senior Data Engineer
with strong expertise in
Azure Databricks, PySpark, and distributed computing
. The role involves developing and optimizing scalable ETL pipelines to support
manufacturing analytics
. You will be working with
high-frequency industrial data
to enable both
real-time
and
batch data processing
.
Key Responsibilities
- Build scalable
real-time and batch data processing workflows
using Azure Databricks, PySpark, and Apache Spark. - Perform
data pre-processing
, including cleaning, transformation, deduplication, normalization, encoding, and scaling, to ensure high-quality inputs for downstream analytics. - Design, implement, and maintain
cloud-based data architectures
, including data lakes, lakehouses, and warehouses, aligned with
Medallion Architecture
. - Deploy and optimize
data solutions
on Azure (preferred), AWS, or GCP, focusing on
performance, security, and scalability
. - Develop and optimize
ETL/ELT pipelines
for structured and unstructured data sourced from
IoT, MES, SCADA, LIMS, and ERP systems
. - Automate workflows using
CI/CD pipelines
and DevOps best practices while ensuring
security and compliance
with industry standards. - Monitor, troubleshoot, and continuously improve
data pipelines
for high availability and reliability. - Utilize
Docker and Kubernetes
for containerized and scalable data processing. - Collaborate closely with
automation teams, data scientists, and engineers
to provide clean, structured data for
AI/ML models
.
Required Skills & Experience
- 4+ years
of proven experience in data engineering, with a strong focus on cloud platforms such as
Azure (preferred), AWS, or GCP
. - Proficiency in
PySpark, Azure Databricks, Python, and Apache Spark
. - Expertise in multiple database technologies, including:
- Relational databases (e.g.,
SQL Server, PostgreSQL
) - Time-series databases (e.g.,
InfluxDB
) - NoSQL databases (e.g.,
MongoDB, Cassandra
) - Hands-on experience with
containerization tools
such as Docker and Kubernetes. - Strong
analytical, problem-solving, and debugging skills
, with meticulous attention to detail. - Excellent
communication and collaboration skills
with a proven track record of effective teamwork. - Comfortable working in a
dynamic, fast-paced startup environment
, with the ability to adapt quickly to changing priorities and responsibilities.
Nice-to-Have Skills
- Familiarity with
MLOps and DevOps practices
, including
model lifecycle management
. - Experience working with
industrial data sources
like IoT, MES, SCADA, LIMS, and ERP.
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