• Design and own the architecture and data flow into the data warehouse • Collaborate with product managers, engineers, and stakeholders • Ensure the platform is performant, scalable, secure, readable and easy to use • Support business-wide data needs and use cases • Design, build, and maintain ELT pipelines • Integrate data from internal systems and external partners • Ensure data quality and accuracy, performance and scalability, secure data handling • Deliver reliable, up-to-date datasets • Develop datasets and data products for internal and external customers

Title: Environmental Chemist - Data Validation Location: United States Job Description: About Us We build careers grounded in purpose, responsibility and real-world impact. "For Planet and Progress" is our north star that guides everything we do. We believe environmental responsibility and human progress are interconnected, interwoven and international. Our scientists, engineers, field teams, consultants and professionals collaborate across disciplines and geographies, guiding industries and governments, ensuring that communities and environments thrive. When you join us, you're not just forging a career, you're joining a movement. A movement for better thinking, smarter solutions and lasting impact. Together, we will advance our way of life and protect the integrity of our environment every step of the way. A Day in the Life This Entry-Level Environmental Chemist - Data Validation position is for entry-level, non-laboratory based environmental chemistry work with an emphasis on environmental analytical data validation. This position can be performed either hybrid out of Valley Forge, PA, or remote. The compensation range for this role is $55,000 - $65,000, commensurate with accomplishments, performance, credentials and geography These requirements reflect the knowledge, skills and abilities that help you do your best work here. - Reviewing analytical data generated by environmental laboratories in an organized and efficient manner, consistent with and as prescribed by corporate and US EPA data validation standard operating procedures, quality assurance project plans, and published analytical methods. - Critically evaluating environmental analytical data to assess usability relative to data quality objectives. - Preparing data quality and usability assessment reports, which will undergo peer review by the project manager and/or senior chemistry staff. - Communicating effectively and professionally, both internally and with external clients and client contractors. - Maintaining confidentiality at all times. - Exercising safe work practices by following all Company safety rules and OSHA regulations, including attendance at all required safety training programs. - Participating in the company's continuous improvement programs and provide support to team efforts. - Staying up-to-date and current by completing formal training and reviewing professional publications. - Performing other duties as assigned depending on your skillset and interests. Your Expertise and Skills These requirements reflect the knowledge, skills and abilities that help you do your best work here: - Bachelor's degree in Chemistry, Environmental Science or an allied science from an accredited college or university. - No experience is required, although 1+ years of environmental analytical data validation or laboratory experience is a plus. - Coursework in analytical chemistry, analytical instrumentation, environmental chemistry, or environmental science is preferred. - Strong understanding of analytical chemistry principles and ability to apply to environmental data usability assessment. - Strong written and verbal communication skills. - Strong analytical and critical thinking skills. - Computer literate - capable of performing tasks such as: creating spreadsheets; composing correspondence; and creating reports and documents using Microsoft Office software. - Strong knowledge of Adobe Acrobat - Meticulous attention to detail and ability to focus on individual tasks while collaborating with your peers. - Ability to define problems, collect data, establish facts, and draw valid conclusions. We are an Equal Opportunity Employer. We are committed to providing access and reasonable accommodation in our employment for individuals with disabilities #LI-LK1 #INDMEG

Role Description We are seeking a detail-oriented individual to join our team at D. H. Radomski Inc. In this position, you will be responsible for accurately entering and managing data to support our operational processes. - Inputting data into various databases and systems with precision. - Reviewing and verifying data to ensure accuracy and completeness. - Maintaining and updating records as necessary. - Assisting with data management tasks and reporting as required. - Collaborating with team members to improve data entry processes. Qualifications - Proven experience in a data entry role or similar position. - Excellent typing skills and attention to detail. - Proficiency in Microsoft Office Suite and data management software. - Strong organisational skills and the ability to manage multiple tasks. - Effective communication skills, both written and verbal. Requirements - Experience with data analysis or reporting tools. - Knowledge of database management. - Ability to work independently and in a team environment.

Role Description We’re looking for an experienced Senior Data Engineer/Analyst to lead the design and delivery of production-grade data platforms, pipelines, and analytics solutions that drive business intelligence and AI/ML capabilities across the organization. In this role, you will own critical data workstreams end to end, make key architectural decisions on data modeling, pipeline design, and platform selection, and collaborate with clients and stakeholders to translate business requirements into scalable data solutions. You will champion modern data stack practices using Snowflake, Databricks, dbt, and cloud-native services, while mentoring other engineers and driving the maturity of our data engineering, analytics, and DataOps capabilities. What You’ll Do - Lead the design, development, and optimization of enterprise-grade data pipelines and transformation layers using dbt, Apache Spark, Airflow, Dagster, and cloud-native orchestration services. - Architect and manage data platforms on Snowflake and/or Databricks, including warehouse design, lakehouse architecture, compute optimization, access governance, and cost management. - Define and enforce data modeling standards across the organization using Kimball dimensional modeling, Data Vault 2.0, Activity Schema, or hybrid approaches. - Design and implement end-to-end data ingestion strategies from diverse sources: transactional databases (CDC via Debezium, Fivetran), APIs, event streams (Kafka, Kinesis, Spark Structured Streaming), SaaS platforms, and unstructured data sources. - Build and maintain curated data products, metrics layers, and semantic models that enable self-service analytics across the organization. - Implement comprehensive data quality, observability, and lineage frameworks using dbt tests, Great Expectations, Monte Carlo, Datafold, Elementary, or Soda. - Collaborate with clients and business stakeholders to gather requirements, translate them into data architecture decisions, and drive technical strategy from ideation to production. - Lead the adoption of DataOps practices including CI/CD for data pipelines (GitHub Actions, dbt Cloud, Databricks Asset Bundles), automated testing, and environment promotion workflows. - Design and optimize analytics solutions and advanced dashboards using Tableau, Looker, Power BI, or Sigma Computing, ensuring performance and usability at scale. - Support AI/ML initiatives by designing and maintaining feature stores, training datasets, and model input/output data pipelines in collaboration with ML engineers. - Mentor junior and mid-level data engineers and analysts, conduct architecture and code reviews, and drive knowledge sharing across the team. - Drive data governance initiatives including cataloging (Alation, Atlan, DataHub, Unity Catalog), lineage tracking, PII management, and regulatory compliance (GDPR, CCPA, HIPAA). Qualifications - Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. - 5–8+ years of professional experience in data engineering, analytics engineering, or a closely related role with significant production delivery. - Deep expertise in SQL and advanced data transformation techniques across analytical databases and data warehouses. - Extensive hands-on experience with Snowflake and/or Databricks in production environments, including architecture design, performance tuning, and cost optimization. - Strong experience with dbt (data build tool) for production-grade transformation, testing, documentation, and CI/CD workflows. - Proficiency in Python (Pandas, PySpark, Polars) and Apache Spark for large-scale data processing. - Experience designing and operating workflow orchestration using Airflow, Dagster, Prefect, or cloud-native equivalents. - Strong knowledge of data ingestion patterns and tools: Fivetran, Airbyte, CDC (Debezium), streaming (Kafka, Kinesis, Flink). - Experience with data visualization and BI platforms: Tableau, Looker, Power BI, or Sigma at enterprise scale. - Proven ability to work directly with clients and stakeholders and translate ambiguous business requirements into concrete data solutions. - Demonstrated ability to mentor engineers, lead design reviews, and influence data architecture direction. - Strong understanding of data governance, cataloging, data quality, and compliance frameworks. Preferred Qualifications - Snowflake SnowPro Advanced or Architect, Databricks Data Engineer Professional, or AWS Data Analytics Specialty certification. - Experience with lakehouse architectures using Delta Lake, Apache Iceberg, or Apache Hudi. - Familiarity with real-time analytics and streaming architectures: Kafka, Spark Structured Streaming, Flink, Materialize, or ksqlDB. - Experience with metrics/semantic layers at scale: dbt Semantic Layer, Cube, MetricFlow, or LookML. - Experience designing data platforms that serve AI/ML workloads, including feature stores (Feast, Tecton), vector databases (Pinecone, Weaviate), and RAG data pipelines. - Familiarity with data mesh or data product architecture patterns in large organizations. - Experience with cloud data infrastructure across AWS (S3, Glue, Athena, Lake Formation, Redshift Serverless), Azure (ADLS, Synapse, Fabric, Purview), or GCP (BigQuery, Dataflow, Dataplex). - Knowledge of cost optimization and FinOps for data platforms (Snowflake credit management, Databricks cluster policies, spot instances). Benefits - Unlimited PTO. - Very generous parental leave, much above industry standards. - Entrepreneurial culture where pushing limits and taking risks is everyday business. - Open communication with management and company leadership. - Small, dynamic teams = massive impact. - Medical, Dental and Vision coverage for employees. - Access to Disability & Life insurance. - Mental health and wellbeing support. - Annual bonus program. - Employer Stock Purchase Program (ESPP). - Yearly Team building experiences. - Mentorship and sponsorship opportunities. - Manager resources and support. Salary Range US East/West Coast: $121,700 - $162,200 Disclaimer: These salary ranges are estimates based on market data. Actual compensation may vary depending on factors including work experience, education, skills, and specific geographic location. Company Description We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic.