RIT Solutions, Inc.
Role Overview:
We are looking for an experienced
Senior Data Engineer
(L7) to design, develop, and optimize large-scale data solutions. You will play a key role in building and enhancing data pipelines, enabling efficient data movement, and supporting advanced analytics and reporting initiatives across business domains. Key Responsibilities:
Lead the end-to-end design and development of
data warehousing solutions
to support enterprise-wide analytics. Develop and optimize
ETL/ELT pipelines
leveraging
SQL, Hadoop, Spark, and Python . Ensure scalability, performance, and reliability of data systems. Mentor and guide junior engineers, providing technical leadership and code reviews. Collaborate with business stakeholders, architects, and analysts to translate requirements into robust data solutions. Work with
Apache NiFi
for data ingestion pipelines and explore automation opportunities. Contribute to cloud migration and adoption strategies, leveraging
cloud-native data platforms
(AWS, Azure, or GCP). Ensure data quality, governance, and security standards are maintained across pipelines. Required Skills & Experience:
5-7 years of experience in
Data Engineering and Data Warehousing
projects. Strong expertise in
SQL
and
programming
(Python or Java/Scala). Solid hands-on experience in
Hadoop ecosystem
and
Apache Spark . Exposure to
Apache NiFi
for data flow management is a strong plus. Good understanding of
cloud concepts
and modern data architectures. Strong problem-solving skills and ability to optimize performance in large datasets. Excellent communication and stakeholder management skills.
Senior Data Engineer
(L7) to design, develop, and optimize large-scale data solutions. You will play a key role in building and enhancing data pipelines, enabling efficient data movement, and supporting advanced analytics and reporting initiatives across business domains. Key Responsibilities:
Lead the end-to-end design and development of
data warehousing solutions
to support enterprise-wide analytics. Develop and optimize
ETL/ELT pipelines
leveraging
SQL, Hadoop, Spark, and Python . Ensure scalability, performance, and reliability of data systems. Mentor and guide junior engineers, providing technical leadership and code reviews. Collaborate with business stakeholders, architects, and analysts to translate requirements into robust data solutions. Work with
Apache NiFi
for data ingestion pipelines and explore automation opportunities. Contribute to cloud migration and adoption strategies, leveraging
cloud-native data platforms
(AWS, Azure, or GCP). Ensure data quality, governance, and security standards are maintained across pipelines. Required Skills & Experience:
5-7 years of experience in
Data Engineering and Data Warehousing
projects. Strong expertise in
SQL
and
programming
(Python or Java/Scala). Solid hands-on experience in
Hadoop ecosystem
and
Apache Spark . Exposure to
Apache NiFi
for data flow management is a strong plus. Good understanding of
cloud concepts
and modern data architectures. Strong problem-solving skills and ability to optimize performance in large datasets. Excellent communication and stakeholder management skills.