big data engineer

ritepros

<div><div><p><b>Big Data Engineer</b> with Bachelor Degree in Computer Science, Computer Information Systems, Information Technology, or a combination of education and experience equating to the U.S. equivalent of a Bachelor&rsquo;s degree in one of the aforementioned subjects.</p>
</div><div><p><b>Job Duties and Responsibilities:</b></p>
<ul><li>Collaborate with System Architects to design, develop, test, and implement efficient Snowflake data models aligned with enterprise data warehousing standards.</li>
<li>Build and manage cloud and hybrid integrations using third-party ETL tools like Azure Data Factory for seamless Snowflake data pipelines.</li>
<li>Maintain CI/CD pipelines in GitHub and Azure DevOps to ensure code quality, version control, and automated deployment for Snowflake solutions.</li>
<li>Conduct SQL performance analysis, query optimization, and database tuning to improve efficiency and scalability in Snowflake models.</li>
<li>Develop robust, scalable Snowflake integrations and data models following industry best practices.</li>
<li>Perform root cause analysis on data model issues and resolve performance bottlenecks to maintain reliable Snowflake systems.</li>
<li>Engage with customers and architects to refine requirements and communicate effectively for business alignment.</li>
<li>Apply strong time management to prioritize concurrent tasks and deliver Snowflake projects promptly.</li>
<li>Use analytical and problem-solving skills to address complex warehouse challenges within the Snowflake ecosystem.</li>
</ul></div><div><p><b>Work experience / Technologies required for the position:</b></p>
<ul><li>At least 5+ years of experience in building and optimizing Big Data, Data pipelines, architectures and data sets.</li>
<li>Experience in performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.</li>
<li>Strong analytic skills related to working with unstructured datasets.</li>
<li>Build processes supporting data transformation, data structures, meta data, dependency and workload management.</li>
<li>A successful history of manipulating, processing and extracting value from large disconnected data sets.</li>
<li>Working knowledge of message queuing, stream processing, and highly scalable Big Data, data stores.</li>
<li>Experience in supporting and working with cross-functional teams in a dynamic environment.</li>
<li>Experience with big data tools: Hadoop, Spark, Kafka, etc.</li>
<li>Experience with relational SQL and NoSQL databases, including AzureSQL and Snowflake.</li>
<li>Experience with Azure cloud services: ADLS, AzureSynapse, Azure Databricks, Delta Lake</li>
<li>Experience with stream-processing systems: Storm, Spark-Streaming, etc.</li>
<li>Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.</li>
</ul></div><p>Work location is Portland, ME with required travel to client locations throughout USA.
<br>
<br>
Rite Pros is an equal opportunity employer (EOE).
<br>
<br>
<b>Please Mail Resumes to:
</b><br>
Rite Pros, Inc.
<br>
565 Congress St, Suite # 305
<br>
Portland, ME 04101.</p>
<p><b>Email: </b><b>resumes@ritepros.com</b></p></div>

Big Data Engineer

<div><div><b>Responsibilities:</b><br>
<ul><li>Design, implement, and optimize data pipelines for batch and real-time data processing using Cloudera (Hadoop, Hive, Spark, Impala) and Informatica (PowerCenter, Cloud Data Integration)</li><li>Build data extraction, transformation, and loading (ETL) workflows using Informatica PowerCenter for large-scale data integration from source systems (e.g., relational databases, flat files, APIs) into Cloudera Data Lake or data warehouse environments.</li><li>Implement Spark jobs on Cloudera for distributed data processing and optimization of data workflows.</li><li>Leverage Informatica for orchestrating ETL workflows, including data extraction, cleansing, transformation, and loading into data repositories (HDFS, Hive, SQL databases, etc.).</li><li>Optimize the Informatica workflows to minimize runtime, ensure smooth data integration, and maintain high data quality.</li><li>Utilize Hadoop and Spark on Cloudera to process large datasets and implement data transformations using MapReduce, Spark SQL, and PySpark.</li><li>Leverage Impala for low-latency SQL queries on Hadoop, ensuring real-time access to processed data.</li><li>Implement partitioning, bucketing, and indexing strategies in Hive and HBase to improve query performance on large datasets.</li><li>Implement and enforce data quality rules within Informatica workflows, ensuring that all transformations meet the required standards for completeness, consistency, and accuracy.</li><li>Ensure compliance with data governance and security protocols (e.g., encryption, masking, access control) in accordance with industry best practices.</li><li>Automation and Scheduling: Automate ETL workflows using Informatica Server, integrating with Airflow, Nifi or other workflow orchestration tools for scheduling and monitoring jobs.</li><li>Utilize Cloudera Navigator for monitoring and auditing data processes within the Hadoop ecosystem.</li><li>Perform regular tuning of the ETL pipelines, data flows, and SQL queries to ensure optimal performance.
</li></ul></div><div><b>Qualifications:</b><br>
<ul><li>Bachelor&rsquo;s degree in Computer Science, Engineering, or related field.</li><li>6+ years of experience in the same field.</li><li>Proven experience with the Cloudera Distribution of Hadoop (CDH), including expertise in HDFS, Hive, Impala, Spark, and HBase.</li><li>Strong hands-on experience with Informatica PowerCenter (ETL), EDC, IDQ, B2B, and Axon.</li><li>Deep understanding of ETL best practices, data pipelines, and distributed computing technologies such as Spark, MapReduce, PySpark, and Hadoop ecosystem components.</li><li>Advanced SQL skills for data manipulation, aggregation, optimization, and reporting across relational and non-relational data stores (e.g., SQL Server, MySQL, PostgreSQL, Hive, Impala).</li><li>Experience in Python and SQL.</li><li>Strong background in data warehousing principles and data modeling, including dimensional modeling (star schema, snowflake schema) and OLAP/OLTP considerations.</li></ul></div></div><p></p>

Senior Big Data Engineer

Edgewater Federal Solutions

<div>Overview:
<p>
The Senior IT Big Data Developer supports the Data Architecture, Technology, and Analytics (DATA) function, enabling advanced data capabilities across enterprise environments. This role is responsible for designing, building, and optimizing scalable data architectures and pipelines that support large-scale analytics, reporting, and mission-critical research initiatives.</p><p></p><p><br>
The ideal candidate is a hands-on data engineer and architect with strong experience in data modeling, pipeline development, and data system optimization. This individual will work closely with technical teams and business stakeholders to ensure reliable, high-performance data delivery that supports complex analytical and operational needs.</p>
Responsibilities:
<ul><li>Design, develop, and maintain scalable data architectures, data pipelines, and data processing frameworks.</li><li>
Expand and optimize data flow, collection, and integration processes across multiple systems and environments.</li><li>
Build and manage ETL/ELT pipelines to ingest, transform, and deliver structured and unstructured data.</li><li>
Develop and maintain databases, data lakes, and enterprise data platforms supporting high-volume workloads.</li><li>
Perform data modeling, schema design, and database optimization to improve system performance and scalability.</li><li>
Collaborate with analysts, economists, and technical teams to support data-driven research and decision-making.</li><li>
Ensure data quality, integrity, and accessibility across enterprise systems.</li><li>
Analyze existing data systems and implement improvements, enhancements, or re-architecture as needed.</li><li>
Support cloud and on-premises data environments, including data migration and pipeline modernization efforts.</li><li>
Provide technical guidance and support to stakeholders on data architecture and best practices.</li></ul>
Qualifications:
<ul><li>Bachelor&rsquo;s degree in Computer Science, Information Technology, Engineering, or related field with <b>7+ years of relevant experience</b> (advanced degree preferred).</li><li>
Strong experience with:
<ul><li>Data architecture and data modeling</li><li>
Database design and administration</li><li>
Building and optimizing data pipelines and workflows</li><li>
Processing large-scale, high-volume datasets</li></ul></li><li>
Proficiency in SQL and at least one programming/scripting language (e.g., Python, R).</li><li>
Experience with ETL/ELT development and data integration frameworks.</li><li>
Experience with distributed data systems, scalable storage solutions, and high-performance data processing.</li><li>
Familiarity with workflow orchestration tools (e.g., Apache Airflow or similar).</li><li>
Experience working in Linux environments and using version control systems (e.g., Git).</li></ul><div></div><div><b><br>
Preferred</b></div><ul><li>
Experience designing enterprise data platforms, data lakes, or cloud-based data solutions.</li><li>
Experience supporting analytics, research, or policy-driven environments.</li><li>
Familiarity with cloud platforms (AWS, Azure, or similar).</li><li>
Strong understanding of data governance, security, and data lifecycle management.</li><li>
Ability to communicate complex technical concepts to both technical and non-technical stakeholders.</li></ul><div></div><div><b><br>
Key Attributes</b></div><ul><li>
Self-directed with a strong service-oriented mindset.</li><li>
Detail-oriented with the ability to manage multiple priorities and stakeholders.</li><li>
Passion for improving and modernizing data systems and architectures.</li><li>
Strong analytical and problem-solving skills.</li></ul><div><b>
Salary: </b>$166,000 - 174,500</div><div></div><div><b><br>
Additional benefits include:</b></div><ul><li>
Paid Time Off &amp; Holiday Pay</li><li>
Medical Insurance</li><li>
Dental Insurance</li><li>
Vision Insurance</li><li>
Disability, Life Insurance, and AD&amp;D</li><li>
Flexible Spending Accounts</li><li>
Pre-Tax 401K and/or After-Tax Roth IRA (with employer matching contribution)</li><li>
Tuition and Technical Training Reimbursement</li><li>
Exercise Reimbursement</li><li>
Computer Reimbursement</li><li>
Employee Assistance Program</li></ul><div><b>
Physical Demands:</b> The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
</div><ul><li>While performing the duties of this job, the employee may be regularly required to stand, sit, talk, hear, reach, stoop, kneel, and use hands and fingers to operate a computer, telephone, keyboard, and standard office equipment</li><li>
Specific vision abilities required by this job include close vision requirements due to computer work</li><li>
The employee must occasionally lift and/or move up to 15 pounds</li><li>
Fine hand manipulation (keyboarding)</li></ul><p></p><p><b><br>
Work Environment: </b><i>The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.</i></p><ul><li>
Exposure to general office conditions while conducting office duties</li><li>
Moderate noise (i.e., business office with computers, phone, and printers, light traffic)</li><li>
Ability to work in a confined area</li><li>
Ability to sit at a computer terminal for an extended period</li></ul><div></div><div><b><br>
Working at Edgewater Federal Solutions:</b></div><div>
Edgewater Federal Solutions is a privately held government contracting firm located in Frederick, MD. The company was founded in 2002 with the vision of being highly recognized and admired for supporting customer missions through employee empowerment, exceptional services, and timely delivery. Edgewater Federal Solutions is ISO 9001, 20000-1, 270001 certified, appraised at CMMI Level 3 Maturity for Development and Services, and has been named in the Top Workplaces in the Greater Washington Area Small Companies since 2018.</div><div></div><p><b><br>
Edgewater Federal Solutions is an Equal Opportunity Employer. It has been and continues to be our policy to provide equal employment to all employees and applicants for employment without regard to race, color, religion, gender, national origin, age, disability, marital status, veteran status and/or other status protected by applicable law.</b></p></div>

Senior IT Big Data Engineer

GSSTech Group

<div><p>We are looking for a highly skilled Data Engineer with strong expertise in PySpark and Informatica Platform Engineering to support enterprise-scale Digital Products and Digital Onboarding initiatives.</p><p>
The ideal candidate should have strong experience in enterprise data engineering, big data ecosystems, data architecture, and modern data management practices within large and complex environments, preferably in banking or financial services.</p><p></p><b><br>
Requirements</b><br>
<br>
Key Responsibilities<ul><li>
Design and develop scalable enterprise data engineering solutions using PySpark and Informatica platforms</li><li>
Build and model Raw Data Vault structures with strong understanding of:</li><li><ul><li>
Source system data structures</li><li>
Data retention policies</li><li>
Data partitioning strategies</li></ul></li><li>
Drive data reusability and reduce data duplication while optimizing performance</li><li>
Define and implement enterprise data architecture standards and best practices</li><li>
Create data exchange standards to support reusable and decoupled architectures</li><li>
Define standards for data archival, retention, and purging</li><li>
Identify and document critical data elements across enterprise source systems</li><li>
Collaborate with data engineers, architects, and source system SMEs to establish data engineering principles and governance standards</li><li>
Support large-scale data transformation and analytics initiatives</li><li>
Contribute to CI/CD-enabled data engineering and deployment environments</li><li>
Ensure compliance with enterprise data quality, governance, and security standards</li></ul>
Required Skills &amp; Experience<ul><li>
Strong hands-on experience in:</li><li><ul><li>
PySpark</li><li>
Informatica Platform Engineering</li><li>
Enterprise Data Engineering</li><li>
Big Data Ecosystems</li></ul></li><li>
Strong expertise in:</li><li><ul><li>
Data Architecture</li><li>
Data Strategy &amp; Roadmaps</li><li>
Enterprise Data Management</li><li>
Data Warehousing &amp; Analytics Solutions</li></ul></li><li>
Strong understanding of:</li><li><ul><li>
Dimensional Modeling</li><li>
Star &amp; Snowflake Schemas</li><li>
Slowly Changing Dimensions (SCD)</li><li>
Role-playing Dimensions</li><li>
Dimensional Hierarchies</li><li>
Data Classification</li></ul></li><li>
Experience transforming traditional Data Warehouse environments into Big Data-based architectures</li><li>
Expertise in:</li><li><ul><li>
Data Quality</li><li>
Data Profiling</li><li>
Data Governance</li><li>
Data Security</li><li>
Metadata Management</li><li>
Data Archival</li></ul></li><li>
Experience with cloud-native principles, architectures, and deployments</li><li>
Strong exposure to Continuous Integration (CI) and Continuous Deployment (CD) environments</li><li>
Strong analytical, troubleshooting, and problem-solving capabilities</li></ul>
Preferred Experience<ul><li>
Banking or financial services domain experience is highly preferred</li><li>
Experience working within enterprise-scale digital transformation programs</li><li>
Exposure to modern analytics and enterprise data platforms</li></ul>
Education<p>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Systems, Information Technology, Engineering, or related field</p>
Preferred Candidate Profile<ul><li>
Ability to work in fast-paced and evolving environments</li><li>
Strong stakeholder collaboration and communication skills</li><li>
Experience handling multiple priorities and enterprise-scale projects</li><li>
Strong ownership mindset and attention to detail</li></ul></div>

Data Engineer - PySpark & Informatica

Chuwa America

<p><b>Job Role: Senior Data Engineer</b><br/><b>Location: </b>Hybrid_ McLean, VA<br/><b>Overview</b><br/>We are seeking an experienced <b>Senior Data Engineer</b> to support enterprise-scale analytics and mission-critical data platforms. The ideal candidate will design, develop, and maintain scalable data pipelines and analytics solutions that transform structured and unstructured data into actionable insights.This role requires strong expertise in modern data engineering, big data ecosystems, cloud-based analytics, and collaborative Agile delivery. The candidate will work closely with analysts, developers, data scientists, and stakeholders in a fast-paced environment supporting high-impact government and defense initiatives. Due to the nature of the work, candidates must possess an active <b>Secret Clearance</b> and be a <b>U.S. Citizen</b>. <b>Key Responsibilities</b></p><ul><li>Design, build, and maintain scalable ETL/ELT pipelines for enterprise analytics platforms</li><li>Develop robust data ingestion, transformation, and orchestration workflows</li><li>Integrate structured and unstructured data from multiple data sources</li><li>Build optimized data models for reporting, analytics, and operational intelligence</li><li>Develop and maintain data applications using Python, SQL, Scala, or R</li><li>Work with distributed computing and big data technologies such as Spark and Hadoop ecosystems</li><li>Implement data quality, governance, monitoring, and performance optimization strategies</li><li>Collaborate with cross-functional teams including:</li><li>Data Scientists</li><li>Analysts</li><li>Software Engineers</li><li>Business Stakeholders</li><li>Support cloud-based and large-scale data processing environments</li><li>Participate in Agile ceremonies, sprint planning, and technical design discussions</li><li>Create documentation, deployment procedures, and operational support materials</li><li>Support secure and compliant handling of sensitive government or defense-related data</li></ul><p><b>Required Skills &amp; QualificationsExperience</b></p><ul><li>5+ years of experience in:</li><li>Data Engineering</li><li>Data Platforms</li><li>Analytics Engineering</li><li>Application Development</li><li>Data Science-related environments</li><li>3+ years of experience:</li><li>Building enterprise-scale data applications</li><li>Designing scalable analytics/reporting systems</li><li>Operationalizing production data pipelines</li></ul><p><b>Technical Skills</b>Strong hands-on experience with:<b>Programming Languages</b></p><ul><li>Python</li><li>SQL</li><li>Scala</li><li>R</li></ul><p><b>Big Data &amp; Distributed Systems</b></p><ul><li>Apache Spark</li><li>Hadoop</li><li>Hive</li><li>Kafka</li><li>Databricks</li><li>AWS EMR</li></ul><p><b>Data Engineering Concepts</b></p><ul><li>ETL / ELT Pipelines</li><li>Data Modeling</li><li>Workflow Orchestration</li><li>Data Warehousing</li><li>Data Transformation</li><li>Data Governance</li><li>Data Quality &amp; Monitoring</li></ul><p><b>Cloud &amp; Analytics Platforms</b></p><ul><li>AWS-based data services</li><li>Enterprise analytics environments</li></ul><p><b>Preferred / Nice-to-Have Skills</b></p><ul><li>Experience with Palantir Foundry</li><li>Experience with visualization tools:</li><li>Tableau</li><li>Power BI</li><li>Qlik</li><li>ArcGIS</li><li>Geospatial analytics experience</li><li>Experience supporting DoD or Combatant Command environments</li><li>Agile/Scrum development experience</li><li>Exposure to machine learning or AI-driven data platforms</li></ul><p><b>Education</b></p><ul><li>Bachelor&rsquo;s Degree in:</li><li>Computer Science</li><li>Data Science</li><li>Mathematics</li><li>Engineering</li><li>Related Technical Field</li></ul><p><b>Security &amp; Compliance RequirementsMandatory</b></p><ul><li>Active Secret Clearance</li><li>U.S. Citizenship Required</li><li>Valid U.S. Passport</li></ul><p><b>Preferred</b></p><ul><li>TS/SCI Clearance</li></ul><p>Pay: $55.00 - $60.00 per hour</p><p>Security clearance:</p><ul><li>Confidential (Required)</li></ul><p>Work Location: Hybrid remote in McLean, VA 22103</p>

Senior Data Engineer_ Only W2 _ Only USC

Prophecy Technologies

<p><b>GCP Data Engineer</b></p><p><b>Location: Preferred location is Charlotte NC , Irving TX, Chandler AZ, Columbus OH , Des Moines and Minneapolis MN (3 days onsite)</b></p><p><b>W2 Candidates</b></p><p><b>Experience with Spark, PySpark, Python, Data Lakehouse architecture, Kafka , Airflow , GCS, Big Query, Cloud Composer, Web based UI development using React and Node JS is a plus</b></p><p>Software Engineer - AI Cloud Native Data Engineering Are you looking for a chance to be part of a high performing team that is passionate about data</p><p>Does the thought of building a modern AI-enabled data platform from the ground up excite you</p><p>We are looking for someone to join our team to help enable solutions for the next generation of data analysis while working in a fast-paced environment that fosters growth and development. If this sounds like you we want to hear from you. We are currently seeking a Lead Cloud Data Platform Engineer to apply deep technical skills to create data products develop AI-based automation tools and build a world-class cloud analytics capability for Wells Fargos Cyber Security Data Ecosystem on a Hybrid cloud. The successful candidate will continually innovate and pioneer the use of new technologies and drive adoption of these amongst a team of talented data engineers. You will be an integral part of our migration from our on-premises systems to the Google Azure cloud. You will be a vital member of an agile team helping to lead the design and hands-on implementation of modern data processing capabilities. This is a visible role that allows you to share your knowledge and skills with other developers and product teams in a collaborative environment. Responsibilities: In this role you will Implement and operationalize modern AI-enabled data capabilities on Google Cloud to ingest transform and distribute data for a variety of big data apps Leverage AI/Agentic frameworks to automate data management governance and data consumption capabilities - data pipelines data quality metadata data compliance etc. Work within a matrix org. with principal engineers product managers and data engineers to roadmap plan and deliver key data capabilities based on priority Required Qualifications: Demonstrable skills recent using AI tools such as LangChain LangGraph/ADK agentic frameworks RAG GraphRAG and using MCP to build agent-based data capabilities 5 years of experience in data engineering including hands-on experience working with Cloud data solutions: creating/supporting Spark based ingestion and processing 3 years of experience with Data lakehouse architecture and design including hands-on experience with Python pySpark Kafka Airflow Google Cloud Storage BigQuery Data Proc Cloud Composer Hands-on experience developing data flows using Kafka Flink and Spark streaming Desired Qualifications: Proven experience using AI to auto-generate data engineering related code context engineering and prompt engineering Deep background on cloud-based data lakes and warehouses and automated data pipelines Public cloud certifications such as GCP Professional Data Engineer Azure Data Engineer or AWS Specialty Data Analytics</p><p>Pay: Up to $70.00 per hour</p><p>Application Question(s):</p><ul><li>This opportunity is strictly W2 and does not support C2C or 1099 engagements. Do you comply with this requirement?</li></ul><p>Experience:</p><ul><li>W2 only. No C2C or 1099. Are you able to comply?: 1 year (Required)</li><li>RAG GraphRAG : 1 year (Required)</li><li>Google Cloud Platform: 6 years (Required)</li></ul><p>Work Location: In person</p>

GCP Data Engineer

<div><p>We are looking for a highly skilled Senior Data Engineer with strong expertise in PySpark, Python, and Big Data technologies to design, build, and optimize scalable data platforms and pipelines. The ideal candidate will work closely with Data Scientists, Business Analysts, and Analytics Delivery teams to develop high-performance analytics solutions and support advanced data science initiatives.</p><b><br>
Requirements</b><br>
<br>
Key Responsibilities<ul><li>
Collaborate with Analytics Delivery Leads and Lead Data Engineers to understand business requirements and deliver impactful data solutions.</li><li>
Work closely with Data Scientists and cross-functional teams to solve complex business problems through data engineering solutions.</li><li>
Manage data onboarding, data access, and stakeholder coordination for analytics initiatives.</li><li>
Design, develop, and maintain scalable, secure, and high-performance data pipelines.</li><li>
Acquire, ingest, process, and transform large-scale structured and unstructured datasets.</li><li>
Implement data engineering best practices for building reliable and production-ready data platforms.</li><li>
Perform data wrangling, cleansing, transformation, and feature engineering for machine learning and analytics use cases.</li><li>
Design and develop modular data pipelines to generate reusable features and modeling datasets.</li><li>
Build and optimize data architectures supporting advanced analytics and machine learning workloads.</li><li>
Contribute to data platform design by selecting appropriate technologies across Big Data, SQL, and NoSQL ecosystems.</li><li>
Ensure data quality, integrity, governance, security, and scalability across the data lifecycle.</li><li>
Participate in Agile squads and collaborate effectively with stakeholders across business and technology teams.</li><li>
Contribute to enterprise data architecture strategy and roadmap aligned with business objectives.</li></ul>
Required Technical SkillsCore Data Engineering<ul><li>
Strong experience in Data Engineering and Big Data solutions.</li><li>
Expert-level proficiency in PySpark.</li><li>
Strong programming experience in Python.</li><li>
Experience building large-scale distributed data processing pipelines.</li></ul>
Data Processing &amp; ETL<ul><li>
Data Ingestion</li><li>
Data Transformation</li><li>
Data Wrangling</li><li>
Data Preparation</li><li>
Data Modeling</li><li>
Feature Engineering</li><li>
ETL/ELT Development</li><li>
Batch Processing</li><li>
Data Pipeline Development</li></ul>
Big Data Technologies<ul><li>
Apache Spark / PySpark</li><li>
Distributed Data Processing Frameworks</li><li>
Big Data Ecosystems</li></ul>
Database Technologies<ul><li>
Strong SQL expertise</li><li>
Experience with Relational Databases</li><li>
Experience with NoSQL Databases</li><li>
Data Warehousing Concepts</li></ul>
Cloud &amp; Analytics Platforms (Preferred)<ul><li>
Azure Data Platform</li><li>
AWS Data Services</li><li>
Google Cloud Data Services</li><li>
Databricks</li><li>
Hadoop Ecosystem</li></ul>
Machine Learning Data Support<ul><li>
Feature Engineering for ML Models</li><li>
Data Preparation for Analytics and AI Use Cases</li><li>
Building Modeling and Feature Tables</li><li>
Supporting Data Science Workloads</li></ul>
Engineering Best Practices<ul><li>
Software Engineering Principles</li><li>
Data Pipeline Optimization</li><li>
Data Quality Management</li><li>
Performance Tuning</li><li>
Scalability &amp; Security</li><li>
Version Control (Git)</li><li>
CI/CD Concepts</li><li>
Documentation Standards</li></ul>
Required Soft Skills<ul><li>
Strong stakeholder management and communication skills.</li><li>
Experience working with Business Analysts, Data Scientists, and Product Teams.</li><li>
Ability to translate business requirements into scalable data solutions.</li><li>
Strong analytical and problem-solving skills.</li><li>
Experience working in Agile/Scrum environments.</li><li>
Ability to work independently and within cross-functional teams.</li></ul>
Preferred Qualifications<ul><li>
Experience working in enterprise-scale data platforms.</li><li>
Experience supporting machine learning and advanced analytics initiatives.</li><li>
Exposure to cloud-native data engineering solutions.</li><li>
Experience designing modern data architectures and data lake environments.</li></ul></div><p></p>

Senior Data Engineer

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