Designs, builds, and optimizes scalable data pipelines, ETL processes, data models, APIs, and cloud-based data infrastructure. The role integrates structured and unstructured data, manages databases, warehouses, lakehouses, and distributed systems, and ensures data quality, security, governance, and performance. Responsibilities also include troubleshooting, technical documentation, architectural contribution, cross-functional collaboration, and mentoring team members.
Summary:
We are seeking a highly skilled and motivated Sr Data
Engineer to join our innovative team. As a Data Engineer, you will be
responsible for designing, building, and maintaining scalable data pipelines
and infrastructure to support our enterprise-wide data-driven initiatives. You
will collaborate closely with cross-functional teams to ensure the
availability, reliability, and performance of our data systems and solutions.
This role involves working across modern data engineering
frameworks, cloud platforms, and distributed environments to enable efficient
data integration, transformation, governance, and consumption across the
organization. You will contribute to architectural decisions, lead complex data
engineering tasks, and support best practices for high‑quality, secure, and
scalable data solutions.
Responsibilities:
Data Pipeline Development
- Design,
implement, and optimize end-to-end data pipelines for ingesting,
processing, and transforming large volumes of structured and unstructured
data.
- Develop
robust ETL (Extract, Transform, Load) processes to integrate data from
diverse sources into our data ecosystem.
- Implement
data validation and quality checks to ensure accuracy and consistency
across systems.
Data Modeling and Architecture
- Design
and maintain data models, schemas, and database structures for analytical
and operational use cases.
- Optimize
data storage and retrieval mechanisms to support performance and
scalability.
- Evaluate
and implement data storage solutions including relational databases, NoSQL
systems, data lakes, and cloud storage platforms.
Data Integration and API Development
- Build
and maintain integrations with internal and external data sources and
APIs.
- Implement
RESTful APIs and web services for secure and efficient data access and
consumption.
- Ensure
compatibility, standardization, and interoperability across systems.
Data Infrastructure Management
- Configure
and manage data infrastructure components including databases, warehouses,
lakehouses, and distributed computing frameworks.
- Monitor
system performance, identify bottlenecks, troubleshoot issues, and
implement optimizations.
- Implement
data security controls, governance, and access management policies to
protect sensitive information.
Collaboration and Documentation
- Collaborate
with data scientists, analysts, and business stakeholders to understand
data requirements and deliver effective technical solutions.
- Document
technical designs, workflows, data flow diagrams, and best practices to
enable transparency and knowledge sharing.
- Provide
technical guidance, mentorship, and support to team members and
cross-functional partners.
Requirements
Requirements:
- Bachelor’s
degree in computer science, Engineering, Information Systems, or a related
field.
- 10+
years of proven experience in data engineering, software development, or
related technical roles.
- 10+
years of experience in programming languages commonly used in data
engineering (Python, Java, SQL, Stored Procedures, Scala, etc.).
- 10+
years of experience with database systems, data modeling, and advanced
SQL.
- 10+
years of experience with ETL tools such as SSIS, Snowflake, Databricks,
Azure Data Factory, Stored Procedures, etc.
- Experience
with big data technologies such as Hadoop, Spark, Kafka, etc.
- 7+
years of experience working with cloud platforms like Azure, AWS, or
Google Cloud.
- Strong
analytical, problem-solving, and debugging skills with high attention to
detail.
- Excellent
communication and collaboration skills in a team-oriented, fast-paced
environment.
- Ability
to adapt to rapidly evolving technologies and business requirements.
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