Data Engineer & Insights Analyst

JPS Tech Solutions Pvt Ltd; Harrisburg (Dauphin County); On-site; USD 120,000 - 160,000; Full time

Job summary

JPS Tech Solutions Pvt Ltd in Harrisburg, PA, seeks an experienced Senior Data Engineer & Insights Analyst to design, build, and maintain scalable data pipelines and analytics solutions for enterprise decision-making.

You will leverage AWS services, SQL, Python, and big data tools to ingest, transform, and load complex datasets, develop dashboards, and collaborate with data scientists and business stakeholders to deliver actionable insights.

Qualifications

• Extensive experience designing enterprise data pipelines and big data architectures.
• 5+ years with AWS data services (S3, EC2, Glue, EMR, Redshift, Athena, Lambda, RDS).
• Strong programming in Python, SQL; experience with Java/C++/Scala is a plus.
• Proficiency in relational and NoSQL databases; data modeling and governance.
• Experience with data orchestration and ETL/ELT pipelines; CI/CD practices.

Responsibilities

• Design, develop, and maintain scalable data pipelines for analytics initiatives.
• Build cloud-based data solutions using AWS services and data orchestration tools.
• Develop dashboards and analytical models for executive audiences.
• Collaborate with data scientists and stakeholders to translate requirements into data products.
• Implement data quality checks, governance, and data lineage.

Skills

Analytical thinking

Problem solving

Project management

Organizational skills

Stakeholder communication

Education

Bachelor's degree

Tools

AWS Cloud Services

Python

R

Java

C++

Scala

SQL & NoSQL Databases

ETL/ELT Tools

Apache Spark

Hadoop

Kafka

Airflow

Informatica / MuleSoft / Talend / TIBCO

REST APIs

Data Modeling

Git & CI/CD

Job description

Job Summary

We are seeking an experienced Senior Data Engineer & Insights Analyst to design, develop, and maintain scalable data pipelines and analytics solutions. The role involves integrating data from multiple sources, transforming complex datasets into reliable and actionable insights, and supporting data-driven decision-making. The ideal candidate will have strong expertise in AWS cloud services, SQL, Python, big data technologies, data modeling, and workflow orchestration, along with experience working with large, complex, and confidential datasets.

Key Responsibilities

• Design, develop, and maintain scalable data pipeline architectures to support enterprise analytics initiatives.
• Build and implement cloud-based data solutions using AWS services such as S3, EC2, Glue, EMR, Redshift, Athena, Lambda, and RDS.
• Develop and maintain data orchestration workflows using Apache Airflow, AWS Step Functions, or similar tools.
• Extract, transform, integrate, and load large datasets from multiple structured and unstructured data sources.
• Build and optimize ETL/ELT processes using SQL, Python, and big data technologies.
• Develop analytical data environments to support statistical analysis, predictive modeling, machine learning, and research activities.
• Collaborate with data scientists, research analysts, and business stakeholders to translate analytical requirements into data solutions.
• Design and develop data models, data structures, metadata, and data integration frameworks.
• Implement data quality checks, validation processes, monitoring, alerting, and logging frameworks.
• Identify data inconsistencies, perform root-cause analysis, and implement improvements to data quality and reliability.
• Develop dashboards, reports, analytical models, and decision-support solutions to communicate actionable insights.
• Support data conversions, migrations, and integrations associated with application modernization and system replacement initiatives.
• Implement data governance, data lineage, security, and privacy controls to ensure responsible data usage.
• Develop and maintain data integration solutions using APIs, messaging systems, and stream-processing technologies.
• Optimize data infrastructure, automate manual processes, and improve pipeline performance and scalability.
• Support cross-functional teams with data-related technical issues and enterprise analytics requirements.

Required Qualifications

• Strong experience designing, building, and optimizing enterprise data pipelines and big data architectures.
• Minimum 5 years of hands-on experience with AWS cloud-based data services, including S3, EC2, Glue, EMR, RDS, Redshift, Athena, Lambda, and DynamoDB.
• Minimum 5 years of experience with programming and scripting languages such as Python, R, Java, C++, or Scala.
• Minimum 5 years of experience with relational SQL and NoSQL databases, including Oracle, Microsoft SQL Server, PostgreSQL, and Cassandra.
• Minimum 5 years of experience with Git, version control systems, and CI/CD pipelines.
• Minimum 5 years of experience with data modeling techniques, including dimensional modeling, Data Vault, and star/snowflake schemas.
• Minimum 5 years of experience with data cataloging and metadata management tools such as AWS Glue Data Catalog.
• Minimum 5 years of experience with data governance, data lineage, and data quality frameworks.
• Minimum 5 years of experience with REST API design and integration patterns.
• Minimum 5 years of experience with big data technologies such as Hadoop, Apache Spark, and Kafka.
• Minimum 5 years of experience with data pipeline orchestration tools such as Apache Airflow, Azkaban, and Luigi.
• Minimum 5 years of experience with data integration platforms such as Informatica, MuleSoft, Talend, or TIBCO.
• Minimum 5 years of experience with stream-processing technologies such as Apache Storm and Spark Streaming.
• Advanced SQL skills and strong understanding of complex queries, relational databases, and data processing techniques.
• Experience developing dashboards, reports, analytical models, and decision-support products for executive and non-technical audiences.
• Strong analytical, problem-solving, project management, and organizational skills.

Preferred Qualifications

• Experience working with higher education student-level data and integrating it with employment, wage, and workforce datasets.
• Experience supporting longitudinal data systems and cross-agency data integration initiatives.
• Experience working with large, complex, disconnected, and confidential datasets.
• Experience supporting statistical research, predictive analytics, machine learning, and evidence-based decision-making.
• Knowledge of data privacy, security controls, data-sharing agreements, and government data governance requirements.
• Experience supporting data conversions related to system modernization and replacement projects.
• Ability to work independently and collaborate with multiple technical, analytical, and business teams.

Core Technical Skills

• AWS: S3, EC2, Glue, EMR, Redshift, Athena, Lambda, RDS, and DynamoDB
• Python, R, Java, C++, and Scala
• SQL, Oracle, Microsoft SQL Server, PostgreSQL, and Cassandra
• ETL/ELT Pipeline Development
• Apache Spark, Hadoop, and Kafka
• Apache Airflow, AWS Step Functions, Azkaban, and Luigi
• Informatica, MuleSoft, Talend, and TIBCO
• Data Modeling and Data Warehousing
• Data Vault and Star/Snowflake Schemas
• AWS Glue Data Catalog and Metadata Management
• Git and CI/CD Pipelines
• REST APIs and Data Integration
• Stream Processing and Real-Time Data Pipelines
• Data Quality, Governance, and Lineage
• Dashboards, Reporting, and Advanced Analytics