Senior Data Engineer / Cloud Data Architect

Cognizant

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Hartford, CT
Salary: $120,000–$130,000 / yr
Posted: 7 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $170k

This role $125k

$109k $223k

below market most similar roles pay here above market

This role pays less than 86% of similar roles. Most pay $126,800–$212,250 — the blue band above. At the midpoint, this role pays about $125k versus about $170k for comparable roles.

Based on 240 similar postings.

Employer

About Cognizant

Cognizant is a multinational IT services and consulting company offering digital transformation, technology, and business process services. It serves clients across financial services, healthcare, manufacturing, and other industries worldwide.

Cognizant currently has 330 open roles on FindRole.

Listed pay typically runs $100,000–$135,000 across 211 roles with salary data.

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View all roles at Cognizant

At a glance

TL;DR · Senior Data Engineer / Cloud Data Architect

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The Senior Data Engineer / Cloud Data Architect will join the team to design, develop, and implement enterprise-scale data solutions within the banking and insurance domains. The role involves translating business requirements into scalable technical solutions by building end-to-end ETL/ELT pipelines with robust error handling and monitoring. Key responsibilities include optimizing data warehouses, data marts, and data lake architectures while designing conceptual, logical, and physical data models for OLTP and OLAP systems. The candidate will utilize a diverse technology stack including Python, SQL, R, Spark, Hive, Kafka, Hadoop, and Snowflake. Expertise in Google Cloud Platform and Amazon Web Services is required, specifically using tools like DBT, Glue, Lambda, and Redshift. Additionally, the role requires implementing CI/CD pipelines using Jenkins and Git-based version control.

Skills

Python SQL Spark Snowflake Hadoop Kafka ETL ELT GCP AWS PostgreSQL SQL Server Hive DBT Jenkins Git MongoDB Elasticsearch Redshift CloudFormation HBase Sqoop R CI/CD

What you'll do

Translate business requirements into scalable technical solutions.
Design and implement end-to-end ETL/ELT data pipelines with robust error handling.
Build and optimize enterprise data warehouses, data marts, and data lake architectures.
Develop scalable data solutions using SQL, Python, and cloud-native technologies.
Design conceptual, logical, and physical data models for OLTP and OLAP systems.
Optimize data processing solutions using Spark, Hive, Kafka, Hadoop, and Snowflake.
Implement CI/CD pipelines and automate deployment processes using Jenkins and Git.
Ensure data quality, governance, security, and performance optimization across enterprise platforms.

What we're looking for

12+ years of experience in designing, developing, and implementing enterprise-scale data solutions.
Experience in Data Engineering, Cloud Platforms, Big Data, ETL/ELT, Data Warehousing, and Business Intelligence.
Experience in the Banking and Insurance domains.
Proficiency in programming languages including Python, SQL, and R.
Expertise in SQL Server, PostgreSQL, MSSQL, and Snowflake.
Proficiency in Google Cloud Platform (GCP) and Amazon Web Services (AWS) technologies.
Experience with Big Data technologies including Hadoop, Hive, Spark, Kafka, Sqoop, HBase, and MongoDB.
Experience with ETL/ELT tools such as Talend, DataStage, and DBT.

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