data pipeline engineer

Seeka Technology

<div>Company Description 
We believe strong early career roles should do more than give someone a job title. They should help people grow into the kind of professionals they want to become. At SEEKA Technologies, we give junior team members meaningful work that builds real capability, sharpens problem-solving, and develops practical experience in fast-moving business and technology environments. Our goal is to help emerging talent strengthen their skills, expand their potential, and prepare for a future shaped by constant innovation across business and IT.
SEEKA Technologies (Not Seeka Limited) is a project under its parent organisation, called Fresh Futures Australia, which is an education consultant based in both Australia and Malaysia. We are developing and creating a platform that utilises A.I. to help match students and job seekers to the right opportunities relevant to them from Kindergarten up to the University, along with vocational training centres and language schools, and of course to businesses and companies who need the right candidates. Our mission is to make it easier for anyone to find, filter and apply to educational institutions and companies in a more seamless manner.
We are currently looking to hire a junior Backend AI &amp; Data Pipeline Engineer who wants to build real-world experience in backend systems, data processing, scraping, retrieval, and cloud-based infrastructure. This role is ideal for someone who already has hands-on technical experience and wants to grow further by working on meaningful engineering challenges that support Yuzee&rsquo;s intelligent matching platform. You will contribute to the systems that process data, power search and matching, and improve the efficiency, reliability, and scalability of our platform.
Below are the important details you will need to take note of:<ul><li>
English is the primary language used in the role</li><li>
This is a full-time remote/work-from-home position</li><li>
We welcome both local and international candidates</li><li>
Candidates should have a degree or proven practical experience relevant to the role</li></ul> 

Job Description 
About the role
We are looking for a Backend AI &amp; Data Pipeline Engineer to own the end-to-end data processing infrastructure that powers Yuzee's intelligent course and job matching platform. You will design and maintain scalable, event-driven pipelines that process tens of thousands of daily records, generate semantic embeddings, and feed a growing knowledge graph used for personalised career pathway recommendations.
What you'll do<ul><li>
Design and maintain three distinct processing pipelines &mdash; scheduled job ingestion, event-driven course processing, and a periodic knowledge graph builder &mdash; each with independent trigger logic and cost controls</li><li>
Generate and manage semantic embeddings via Amazon Bedrock (Titan v2), index them in MongoDB Atlas Vector Search, and calibrate similarity thresholds to ensure match accuracy</li><li>
Build and maintain a knowledge graph linking jobs, courses, skills, and industries using FP-Growth association rules and archetype-to-SOC code mapping</li><li>
Build and improve a two-stage discovery and matching API on AWS Lambda &mdash; vector retrieval first, then deep eligibility scoring with LLM re-ranking</li><li>
Right-size Fargate Spot instances and design resumable processing loops that tolerate interruption, keeping infrastructure costs under control as data volume scales</li><li>
Maintain and improve daily job scrapers across multiple sources and build institution data scrapers with robust HTML cleaning pipelines</li></ul>
What we're looking for<ul><li>
1+ years of backend engineering experience focused on data pipelines, ML infrastructure, or search systems</li><li>
Hands-on experience with AWS serverless and container services &mdash; Lambda, ECS Fargate, EventBridge, and Step Functions</li><li>
Strong Python skills &mdash; Pandas, async processing, bulk database operations, and text cleaning</li><li>
Familiarity with vector databases and semantic similarity search; MongoDB Atlas Vector Search experience is a strong plus</li><li>
Cost-conscious infrastructure mindset &mdash; you think in per-record compute costs, free tiers, Spot resilience, and right-sizing</li><li>
Ability to document and communicate complex architecture clearly to both technical and non-technical stakeholders</li></ul>
Nice to have<ul><li>
Experience with knowledge graphs or association rule mining (FP-Growth, Apriori)</li><li>
Experience using LLMs for re-ranking or eligibility assessment on top of vector retrieval results</li><li>
Background in edtech, jobtech, or recommendation/matching systems</li></ul> 

Qualifications 
Degree or existing proven experience 
Additional Information 
Use this instead:
Benefits<ul><li>
Fully remote / work-from-home role</li><li>
Flexible working hours within the team&rsquo;s expected schedule and business needs</li><li>
Opportunity to work on real backend, data, and AI infrastructure projects</li><li>
Exposure to practical engineering challenges in scraping, pipelines, retrieval, and cloud systems</li><li>
Ongoing growth and development within a fast-moving technology environment</li><li>
Opportunity to build long-term value and grow with the company based on performance, including progression and increased responsibility over time</li></ul>
A slightly more polished version:
Benefits<ul><li>
Fully remote / work-from-home position</li><li>
Some flexibility in working hours, depending on team requirements and deliverables</li><li>
Hands-on experience working on meaningful backend, data pipeline, and AI-related systems</li><li>
Opportunity to contribute to a growing platform with real product and engineering challenges</li><li>
Professional growth in a practical, fast-paced environment</li><li>
Strong potential for long-term progression based on performance, regardless of location</li></ul>
If you want it to sound more attractive for hiring, the strongest version would be to add things like:<ul><li>
ownership</li><li>
real product impact</li><li>
career growth</li><li>
direct exposure to architecture and scaling decisions</li></ul></div>

Backend AI & Data Pipeline Engineer

Worldpac

<div>Opportunity Information:

Overview:
Worldpac, a leading name in automotive parts distribution, is looking for a results-driven Sr. Data Engineer to help build the robust and scalable data pipelines and infrastructure that underpin our digital transformation and AI initiatives.
The Data Engineer will play a critical role in designing, implementing, and maintaining data infrastructure that supports data science, analytics, and operational systems across Worldpac&rsquo;s core business functions. This role focuses on developing production-grade data pipelines that integrate with a wide range of systems&mdash;from modern APIs to legacy databases&mdash;ensuring data is reliable, clean, and ready for downstream use.
Ideal candidates will bring a strong foundation in data engineering, experience working with cloud and legacy systems, and a passion for applying best practices in data architecture, software development, and automation. This position will be onsite at our Corporate HQ in Oak Brook, IL 5 days/week. 
Responsibilities:
Data Pipeline Development and Management:<ul><li>
Build and maintain robust ETL/ELT pipelines to ingest data from diverse systems (ERP, CRM, supply chain, sales, external APIs, etc.).</li><li>
Create and manage synthetic and derived features to support AI and analytics use cases.</li><li>
Ensure data quality, consistency, and lineage across all pipeline stages.</li></ul> 
Systems Integration and Modernization:<ul><li>
Connect legacy systems and databases with modern cloud-based platforms (e.g., Snowflake, Databricks, AWS).</li><li>
Engineer real-time and batch data flows, including support for streaming data where appropriate (e.g., Kafka, Kinesis).</li><li>
Partner with IT to improve access to core systems and modernize data interfaces.</li></ul> 
Data Governance and Reliability:<ul><li>
Implement monitoring, validation, and observability frameworks for data flows.</li><li>
Ensure compliance with data privacy, retention, and security policies.</li><li>
Maintain documentation for data sources, transformations, and pipeline dependencies.</li></ul> 
Collaboration and Enablement:<ul><li>
Work closely with data scientists and analysts to translate business and model requirements into engineered datasets.</li><li>
Create reusable data assets and modular pipelines to support experimentation and production deployment.</li><li>
Contribute to team standards for code quality, version control, and DevOps practices.</li></ul> 
Qualifications:
<ul><li>Education: Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or a related technical field</li><li>
Must-Have Skills:
</li><li>10+ years of experience in data engineering or software development with a focus on data</li><li>
Proficient in SQL and Python (or Scala) for developing data workflows and transformations</li><li>
Hands-on experience with cloud data platforms (e.g., Snowflake, Databricks, BigQuery, Redshift)</li><li>
Experience with orchestration tools (e.g., Airflow, Prefect, Dagster) and CI/CD pipelines</li><li>
Solid understanding of data warehousing concepts, schema design, and performance optimization</li><li>
Ability to work with structured and unstructured data across batch and streaming paradigms</li></ul>
Location Type: On-Site Pay Range: USD $103,500.00 - USD $138,000.00 /Yr.</div>

Sr. Data Engineer

International Rescue Committee

<div>The International Rescue Committee (IRC) responds to the world's worst humanitarian crises, helping to restore health, safety, education, economic wellbeing, and power to people devastated by conflict and disaster. Founded in 1933 at the call of Albert Einstein, the IRC is one of the world's largest international humanitarian non-governmental organizations (INGO), at work in more than 40 countries and 29 U.S. cities helping people to survive, reclaim control of their future and strengthen their communities. A force for humanity, IRC employees deliver lasting impact by restoring safety, dignity and hope to millions. If you're a solutions-driven, passionate change-maker, come join us in positively impacting the lives of millions of people world-wide for a better future.
Technology and Operations support the organization's work by providing reliable and scalable solutions for the IRC's offices around the world. The Data Team at IRC is responsible for the design and delivery of global data strategies and the systems and products that deliver on it. 
Job Overview / Summary 
The Data Engineer will support the implementation, configuration, and maintenance of data pipelines and transformation workflows across IRC's data environment. This role plays an active part in building and operating ELT processes, dbt models, and cloud-based data platforms including Azure Databricks and the IRC Lakehouse. 
The successful candidate has foundational to growing expertise in dbt, SQL, and Databricks, and is eager to take on increasing ownership of data engineering deliverables. Working closely with senior engineers and the Data Architect, this role contributes to data modeling, pipeline development, and platform reliability in a collaborative and fast-paced environment. 
Major Responsibilities<div> 
Pipeline Engineering &amp; Orchestration 
<ul><li>Build and maintain ELT data pipelines using Databricks Workflows and Azure Data Factory for batch and scheduled processing from internal and external sources.</li><li>Support the ingestion of data from key systems (e.g., D365 CRM, ServiceNow) into Lakehouse.</li><li>Monitor pipeline execution, identify failures, and troubleshooting issues in collaboration with senior engineers.</li><li>Contribute to pipeline documentation and help maintain runbooks and process standards.</li></ul></div><div> 
dbt Development 
<ul><li>Develop and maintain dbt models across staging, intermediate, and mart layers under the guidance of senior team members.</li><li>Write dbt tests and contribute to source freshness checks to support data quality.</li><li>Learn and apply dbt best practices including modular design, ref dependencies, and incremental model patterns.</li><li>Work with analysts and business teams to translate data requirements into dbt models.</li></ul></div><div> 
SQL &amp; Data Transformation 
<ul><li>Write intermediate to advanced SQL for data extraction, transformation, and validation tasks.</li><li>Apply SQL techniques including joins, CTEs, window functions, and aggregations to support reporting and analytics needs.</li><li>Assist in query optimization and performance troubleshooting within</li></ul></div><div>
Databricks SQL environments. 
<ul><li>Support data model maintenance and help accommodate new source fields or schema changes.</li></ul></div><div> 
Databricks &amp; Cloud Platform 
<ul><li>Develop and maintain Databricks notebooks and jobs for data transformation workloads.</li><li>Gain hands-on experience with Delta Lake concepts and PySpark for data processing.</li><li>Follow Lakehouse design patterns (Bronze/Silver/Gold) as defined by the Data Architect.</li><li>Support cloud resource management including basic cluster configuration and job scheduling.</li></ul></div><div> 
Collaboration &amp; Learning 
<ul><li>Actively collaborate with the Data Team on pipeline design, troubleshooting, and delivery.</li><li>Participate in code reviews and incorporate feedback to improve code quality.</li><li>Support documentation of processes, standards, and data flows.</li><li>Engage with Finance, FP&amp;A, and other business teams to understand data needs and assist in solution delivery.</li></ul></div><div> 
Key Working Relationships 
<ul><li>Data Team (Data Architect, Lead Data Engineer, Data Analysts)</li><li>Business / Departmental Priority Setters (Finance, FP&amp;A, Operations)</li><li>Enterprise Systems Owners (D365 CRM, Integra)</li></ul>
Position Reports To</div> 
Lead Data Engineer 
Position Supervises: None 
Travel Requirements 
Special projects may require travel to enable on-the-ground learning to support data strategy deliverables. 
Minimum Requirements<div> 
Experience 
<ul><li>3&ndash;6 years of hands-on experience in data engineering, analytics engineering, or a related technical role.</li><li>Demonstrated experience building or maintaining data pipelines in a professional setting.</li><li>Exposure to cloud-based data platforms, preferably Azure (Databricks, Data Factory, or Synapse).</li></ul></div><div> 
Technical Skills &mdash; Required 
dbt: 
<ul><li>Working knowledge of dbt model development including staging and mart layers.</li><li>Familiarity with dbt tests, documentation, and source configurations.</li><li>Eagerness to deepen dbt skills including incremental models and CI/CD integration.</li></ul></div><div> 
Databricks: 
<ul><li>Hands-on experience with Databricks notebooks and basic job/workflow setup.</li><li>Familiarity with Delta Lake concepts and Databricks SQL.</li><li>Exposure to PySpark for data transformation tasks.</li></ul></div><div> 
SQL: 
<ul><li>Solid SQL skills: joins, CTEs, window functions, aggregations, and basic performance awareness.</li><li>Experience writing SQL for data transformation and validation in a cloud data warehouse.</li></ul></div><div> 
Pipeline Engineering: 
<ul><li>Experience building or supporting ELT pipelines with monitoring and basic data validation.</li><li>Familiarity with pipeline orchestration tools such as Azure Data Factory or Databricks Workflows.</li></ul></div><div> 
Python: 
<ul><li>Basic to intermediate Python skills for data processing, scripting, and automation.</li><li>Familiarity with PySpark is a plus.</li></ul></div><div> 
Data Modeling: 
<ul><li>Understanding of star/snowflake schemas and fact &amp; dimension table concepts.</li><li>Exposure to Lakehouse or medallion architecture (Bronze/Silver/Gold) is a plus.</li></ul></div><div> 
Soft Skills 
<ul><li>Curious and eager to learn with a proactive approach to problem-solving.</li><li>Good communication skills &mdash; able to collaborate across technical and non-technical teams.</li><li>Attention to detail and a strong sense of data quality.</li><li>Comfortable working in a collaborative, fast-paced, and remote team environment.</li></ul></div><div> 
Preferred Additional Requirements 
<ul><li>Experience with Databricks or Azure Synapse Analytics.</li><li>Familiarity with D365 CRM or Similar data structures.</li><li>Exposure to Git-based workflows and CI/CD practices for data pipeline deployments.</li><li>Experience in a humanitarian, nonprofit, or international development context.</li></ul></div> 
Working Environment 
Remote 
PROFESSIONAL STANDARDS
All International Rescue Committee workers must adhere to the core values and principles outlined in IRC Way - Standards for Professional Conduct. Our Standards are Integrity, Service, Equality and Accountability. In accordance with these values, the IRC operates and enforces policies on Safeguarding, Conflicts of Interest, Fiscal Integrity, and Reporting Wrongdoing and Protection from Retaliation. IRC is committed to take all necessary preventive measures and create an environment where people feel safe, and to take all necessary actions and corrective measures when harm occurs. IRC builds teams of professionals who promote critical reflection, power sharing, debate, and objectivity to deliver the best possible services to our clients.
Cookies: https://careers.rescue.org/us/en/cookiesettings
#li-1</div>

Data Engineer

Hire Hangar

<div>Join Hire Hangar and work with fast-growing global companies while building a long-term, remote career.
Job Title Data Engineer &ndash; Tech Industry
Location Remote
Time Zone US Time Zones (EST&ndash;PST)
Role Overview We are seeking a skilled and detail-oriented Data Engineer to design, build, and maintain scalable data infrastructure for a fast-growing tech company. This is a full-time role requiring deep technical expertise in data pipelines, warehousing, and architecture. The ideal candidate is analytical, collaborative, and comfortable working across large datasets while partnering with data science, product, and engineering teams to deliver reliable, high-quality data solutions.
Key Responsibilities<ul><li>
Design, build, and maintain robust, scalable data pipelines and ETL/ELT workflows</li><li>
Develop and manage data warehousing solutions to support business intelligence and analytics needs</li><li>
Ensure data quality, integrity, and availability across all data systems and sources</li><li>
Collaborate with data scientists, analysts, and product teams to understand and fulfill data requirements</li><li>
Optimize query performance and database architecture for speed and efficiency</li><li>
Monitor, troubleshoot, and resolve data pipeline failures and incidents</li><li>
Implement and enforce data governance, security, and compliance best practices</li><li>
Document data models, processes, and infrastructure to support team knowledge sharing</li></ul>
Required Qualifications<ul><li>
4+ years of experience as a Data Engineer or in a similar data infrastructure role within a tech company (non-negotiable)</li><li>
Strong proficiency in SQL and at least one programming language such as Python or Scala</li><li>
Hands-on experience building and managing ETL/ELT pipelines using tools such as Apache Airflow, dbt, or similar</li><li>
Experience with cloud data platforms such as AWS, GCP, or Azure, and data warehouses such as Snowflake, BigQuery, or Redshift</li><li>
Solid understanding of data modeling, schema design, and database optimization</li><li>
Strong problem-solving skills with the ability to manage complex, high-volume data environments</li><li>
Must have prior remote work experience, be fluent with remote collaboration tools and platforms (such as Slack, Zoom, Google Workspace, Asana, or similar), and have ideally worked with US or UK-based companies. Applications without this experience will not be considered.</li></ul>
Preferred Qualifications<ul><li>
Experience with real-time or streaming data pipelines using tools such as Kafka or Spark</li><li>
Familiarity with data lakehouse architectures (e.g., Delta Lake, Apache Iceberg)</li><li>
Exposure to machine learning workflows and supporting ML data infrastructure</li><li>
Experience working in an Agile or DevOps environment with CI/CD practices applied to data workflows</li></ul>
Tools &amp; Technology<ul><li>
Python, SQL, or Scala</li><li>
Apache Airflow, dbt, or equivalent pipeline orchestration tools</li><li>
Snowflake, BigQuery, or Redshift</li><li>
AWS, GCP, or Azure</li><li>
Kafka or Spark (advantageous)</li><li>
Google Workspace</li><li>
Slack, Zoom, Jira, and other remote collaboration tools</li></ul>
Please NOTE
It is crucial that you complete the application form in full. As part of the application process, you will be required to record a video. If your application is successful, you will receive an email confirming next steps&mdash;the video is the first step of the interview process. If you do not record a video, we will not be able to consider you for ANY open roles.
We connect top talent with vetted employers, competitive pay, and real growth opportunities.</div>

ACME ONE

About the RoleWe're looking for a motivated Data Engineer with hands-on experience in SQL Server, SSIS, Azure cloud data tools, and Power BI. You'll help build and maintain data pipelines, support cloud-based integrations, and contribute to BI solutions that actually matter.Key Responsibilities<ul><li>Develop, optimize, and maintain ETL/ELT pipelines across on-premises and Azure environments</li><li>Design and manage SQL Server objects &mdash; tables, views, stored procedures, and functions</li><li>Build data ingestion and transformation solutions using SSIS, ADF, ADLS, Azure Synapse, and Databricks (basic exposure is a plus)</li><li>Create and manage Power BI datasets, dataflows, DAX measures, and interactive dashboards</li><li>Ensure data quality, reliability, and timely availability across systems</li><li>Troubleshoot pipeline failures, performance issues, and data inconsistencies</li><li>Collaborate with analysts and business users on reporting requirements</li><li>Document workflows, data models, and SOPs</li></ul>Requirements<ul><li>2-3 years of experience as a Data Engineer, BI Developer, or similar</li><li>Strong MS SQL Server &amp; T-SQL skills</li><li>Hands-on with Azure tools &mdash; ADF, ADLS, Synapse</li><li>Power BI proficiency &mdash; reports, dashboards, DAX, data modeling</li><li>Solid understanding of ETL/ELT and star/snowflake data modeling</li></ul>Job Type: Full-timeApplication Question(s):<ul><li>What is your current salary?</li><li>What is your expected salary?</li><li>We are located near UCP, are you comfortable with the location?</li></ul>Work Location: In person

Data Engineer - Analytics

Cloud Enterprise Business Solutions (CEBS)

<div>
 
 
 Data Engineer
 
 
 
 We are looking for a Data Engineer with strong experience in Azure data services, Azure Databricks, PySpark, and Power BI to join our customer analytics and insights team. You will play a key role in bridging the gap between business requirements and technical delivery working across data engineering, analytics, and stakeholder communication.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Work closely with business stakeholders to gather, understand, and translate business requirements into scalable data solutions.
 </li>
 <li>
 Design, build, and optimize data pipelines in Azure Databricks using PySpark and SQL.
 </li>
 <li>
 Collaborate with analysts and product owners to deliver ad-hoc analyses, as well as end-to-end production-grade data solutions.
 </li>
 <li>
 Manage and maintain data lakes, ensuring efficient data ingestion, transformation, and storage.
 </li>
 <li>
 Develop data models and datasets optimized for Power BI dashboards and self-service analytics as well as design and create dashboards.
 </li>
 <li>
 Participate in CI/CD and DevOps processes for automated deployment and monitoring of data workflows.
 </li>
 <li>
 Communicate technical concepts effectively to non-technical business users, providing clarity and actionable insights.
 </li>
 </ul>
 
 
 
 
 
 Key Qualifications
 
 
 <ul>
 <li>
 3+ years of experience as a Data Engineer. Experience in Azure data ecosystem (Azure Data Factory, Azure Data Lake Gen2, Azure Databricks) is a plus.
 </li>
 <li>
 Strong hands-on experience in PySpark, SQL, and Python for data transformation and pipeline automation.
 </li>
 <li>
 Experience designing and managing data pipelines and ETL processes using Databricks and Delta Lake.
 </li>
 <li>
 Experience in Data Visualization and a good understanding of Power BI data.
 </li>
 <li>
 Experience in stakeholder management. Translating business needs into data-driven solutions and presenting findings clearly.
 </li>
 <li>
 Familiarity with DevOps concepts, Git, and CI/CD pipelines in Azure DevOps.
 </li>
 <li>
 Solid understanding of data governance, data quality, and metadata management principles.
 </li>
 </ul>
 
 
 
 
 
 What&rsquo;s in it for you
 
 
 <ul>
 <li>
 Competitive salary
 </li>
 <li>
 Employees' Provident Fund, medical and other incentives
 </li>
 <li>
 Unique working environment where you communicate and work directly with international clients
 </li>
 <li>
 Self-development opportunities
 </li>
 </ul>
</div>

Zoolatech

<div><div><div><div><div><div><div><div>OVERVIEW</div>
</div><div><div>RESPONSIBILITIES</div>
</div><div><div>REQUIREMENTS</div>
</div></div></div></div><div><div><div>Our client is a global jewelry manufacturer that is transforming its data and analytics footprint and is also on a journey from IaaS-based Microsoft/QV solutions to Azure PaaS.
As a Data Engineer, you will collaborate with product owners, architects, and other key profiles across the global organisation. You will help business verticals and clusters maximize the value of the data and drive business change as a result.
Your primary focus will be building and implementing scalable data products on the global data platform together with other smart engineers in the organization.
</div><div><ul><li>Work closely with your colleagues within a product team to design scalable, efficient, and stable products</li><li>
﻿﻿Work closely with product owners to build and deliver features designed to drive commercial business cases and efficiencies within reporting and analytics, and other data-driven use cases</li><li>
﻿﻿Create and maintain a high-quality data pipeline architecture</li><li>
﻿﻿Obtain relevant business and system knowledge to convert requirements efficiently to technical design documentation and conceptual data modelling</li><li>
﻿﻿Ingest large, complex data sets, automate manual processes, optimize data delivery, improve data quality, etc.</li><li>
﻿﻿Own your data products and track continuous stability and benefits</li><li>
Live and breathe &quot;build -once-consume-many&quot; culture in which we enable others to use our data products for maximum value-add</li><li>
﻿﻿Work with stakeholders and teams to assist with data-related technical challenges</li><li>
﻿﻿Follow best practice and existing guidelines, but also push the limits</li><li>
﻿﻿Thrive in a fast-paced environment, and you get motivated by challenges as a true problem solver.</li></ul>
</div><div><ul><li>Relevant education within Computer Science, Mathematics, Economics, Information Management, or Statistics</li><li>
﻿﻿3+ years of experience as a Data Engineer or in a Software engineering role with a focus on data</li><li>
﻿﻿Proven experience with ADF, Data Lake, Synapse, T/U-SQL, Databricks, MDS, DAX, SSIS, and SQL Server</li><li>
﻿﻿Experience with at least one object-oriented or functional/scripting language - Java, Scala, Python, etc.</li><li>
DevOps and CI/CD focus</li><li>
Hands-on with git and coding best practices</li><li>
Unit testing</li><li>
Experience in working with relational data sets using SQL</li><li>
Experience with data warehousing, dimensional modelling, and cubes</li><li>
﻿﻿Experience in building and optimizing data pipelines, architectures, and datasets</li><li>
﻿﻿Experience in working with Azure, AWS, or other cloud providers</li><li>
Designed, built, and delivered production-ready data products at an enterprise level</li><li>
Highly proficient in English and able to communicate with all levels</li><li>
﻿﻿Agile mindset and experience of Scrum</li></ul>
It's a plus if you have worked with:<ul><li>
﻿﻿Big data: Spark, Hadoop</li><li>
﻿﻿Data pipeline and workflow tools: Airflow</li><li>
﻿﻿Infrastructure: Kubernetes and Helm; we're using Airflow running on Kubernetes</li><li>
﻿﻿Stream-processing systems: Kafka or Spark Streaming</li></ul>
</div></div></div><div><div><div><div>Location:
<div>Istanbul, Turkey
</div></div><div>Seniority:
<div>Middle
</div></div><div>Technologies:
<div>Data
</div></div></div></div><div><div>Benefits:
<ul><li>Paid Vacation
</li><li>Hybrid Work (home/office)
</li><li>Sick Days
</li><li>Sport/Insurance Compensation
</li><li>Holidays Day Off
</li><li>English Classes
</li><li>Training Compensation
</li><li>Transportation compensation</li></ul></div></div></div></div></div></div>

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10000 data pipeline engineer jobs Near Me

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