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# Data Engineer II

- **Company:** TEKSYSTEMS INC.
- **Location:** Hanover, MD, United States
- **Experience:** Experienced
- **Salary:** $78,400.0 - $117,600.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon S3, Business Analytics Applications, ARM Architecture, BigQuery, Cloud Computing, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Warehousing, Distributed Computing Environment, Data Flow Control, Python (Programming Language), Machine Learning, Performance Tuning, Power BI, DataOps, Cloudera, Azure Data Lake, SQL Databases, Data Storage Technologies, Data Ingestion, Azure Data Factory, Snowflake, Data Lakes, Pyspark, Information Technology, Data Analytics, AWS Data Analytics, Data Management, Amazon Simple Queue Service (SQS), Azure Synapse Analytics, Data Pipelines, Databricks
- **Published:** October 23, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3466572302&tx=CT3129TTT&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

The ideal candidate should be a good team player with 3-5 years of experience in data engineering developing scalable and efficient ETL pipelines processing different formats of data (structured, semi-structured and unstructured) following the data engineering best practices.

This role requires curiosity, ability to thrive in a fast and evolving environment, effective communication, and deep expertise in developing, and deploying scalable, and high-performance cloud-native data solutions, under the guidance of architects, and team leaders., * Bachelors degree in computer science, Engineering, or related field.

 * 3-5 years of experience in Data Engineering developing production-grade data ingestion, transformation, and orchestration solutions.
 * Strong proficiency in SQL and Python (PySpark proficiency will be an added advantage).
 * Strong hands-on experience building data pipelines
 * Experience working with different data sources (structured, semi-structured, and unstructured).
 * Strong hands-on capability in at least one of the following platform areas
 * AWS Data Engineering (S3, Glue, Redshift, Lambda, Kinesis, SNS/SQS, EMR, Athena, Quicksight)
 * Azure Data Engineering (ADLS Gen2, Fabric, Synapse, Databricks, Power BI)
 * GCP Data Engineering (BigQuery, Data Storage, Dataproc, Pub/Sub, Dataflow, Datastream)
 * Snowflake (Snowpipe, Streams and Tasks, COPY command, dynamic tables, timetravel, Snowpark, Cortex)
 * Matillion (pipeline design, orchestration, parameterization, environment promotion, error handling, and operational monitoring)
 * Databricks
 * Informatica / IICS
 * Curious and growth mindset, meticulous, strong problem-solving, and excellent verbal and written communication skills
 * Passion for staying updated with the latest cloud and AI/ML technologies and ability to evaluate and adopt emerging tools and methodologies., * Matillion data engineering certifications such as:
 * Matillion ETL Foundations Certification
 * Matillion Data Productivity Cloud Foundations Certification
 * Snowflake certifications such as:
 * SnowPro Core Certification
 * SnowPro Advanced: Data Engineer
 * Good Understanding of data modelling (Star/Snowflake) and performance tuning

## Description

We are seeking a highly skilled and talented Intermediate level Data Engineer with strong hands-on data engineering proficiency (modern cloud data engineering, data integration, distributed processing, orchestration, and DataOps practices) to develop and maintain modern, scalable data platforms. Past experience in Snowflake and Matillion is preferred but not mandatory., * Under the guidance from architect/lead, actively involves in requirement gathering from customers, ideating, and implementing the technical solutions

 * Collaborates closely with architects/leads and other stakeholders to identify the appropriate tools/technologies and implement the data management solutions
 * Develop scalable data ingestion, transformation, and orchestration pipelines following modern principles and industry best practices for data lake or data warehouse / analytics solutions in an on-prem or cloud native architecture
 * Builds all data management/analytics solutions following applicable Info-sec, quality control, and governance/maintenance standard
 * Complies with all internal and external (project specific) operational, compliance and governance processes.
 * Implement CI/CD pipelines for data and analytics workloads